Dynamic transcriptome analysis measures rates of mRNA synthesis and decay in yeast

Saccharomyces cerevisiae recovery from various mild abiotic stresses: Viability, fitness, and high resolution three-dimensional morphology imaging

Environmental conditions have a huge impact on the development of all living things but are especially important in the case of single-celled organisms such as Saccharomyces cerevisiae that must respond quickly and appropriately to any change. Many molecular mechanisms of response to stress have been identified in yeast, but only a few reports address physiological and morphological changes. To investigate S. cerevisiae recovery from ten mild stress conditions and to describe the viability and fitness, we performed a series of growth analysis experiments. Moreover, label-free live cell imaging of yeast subjected to ten environmental stresses has been achieved using holotomography - a leading-edge high resolution 3D quantitative phase imaging. We determined that recovery times of yeast cultures subjected to hyperosmotic and sugar starvation stresses were the shortest, as were the doubling times. Substantially lower proliferation capacity was recorded in yeast after applying sugar- and AA starvation, and high pH stresses, compared to control. Furthermore, the stationary growth was much shorter after subjecting yeast to hypoosmotic and heat stresses, and much longer after anaerobic and UV stresses. Further, we determined changes in shape, colony formation, cell wall damage, volume, sphericity, protein and lipid contents in yeast cells under stress conditions. The most prominent changes were observed for UV and hyperosmotic stresses. Condluding, stress conditions applied to yest cultures affected them differently, causing detrimental effects to their growth, metabolism, fitness and morphology. Moreover, we have proven that holotomography is excellent for precisely determining morphological changes of single cells.

Transient power-law behaviour following induction distinguishes between competing models of stochastic gene expression

What features of transcription can be learnt by fitting mathematical models of gene expression to mRNA count data? Given a suite of models, fitting to data selects an optimal one, thus identifying a probable transcriptional mechanism. Whilst attractive, the utility of this methodology remains unclear. Here, we sample steady-state, single-cell mRNA count distributions from parameters in the physiological range, and show they cannot be used to confidently estimate the number of inactive gene states, i.e. the number of rate-limiting steps in transcriptional initiation. Distributions from over 99% of the parameter space generated using models with 2, 3, or 4 inactive states can be well fit by one with a single inactive state. However, we show that for many minutes following induction, eukaryotic cells show an increase in the mean mRNA count that obeys a power law whose exponent equals the sum of the number of states visited from the initial inactive to the active state and the number of rate-limiting post-transcriptional processing steps. Our study shows that estimation of the exponent from eukaryotic data can be sufficient to determine a lower bound on the total number of regulatory steps in transcription initiation, splicing, and nuclear export.

Transcriptional heterogeneity shapes stress-adaptive responses in yeast

In response to stress, cells activate signaling pathways that coordinate broad changes in gene expression to enhance cell survival. Remarkably, complex variations in gene expression occur even in isogenic populations and in response to similar signaling inputs. However, the molecular mechanisms underlying this variability and their influence on adaptive cell fate decisions are not fully understood. Here, we use scRNA-seq to longitudinally assess transcriptional dynamics during osmoadaptation in yeast. Our findings reveal highly heterogeneous expression of the osmoresponsive program, which organizes into combinatorial patterns that generate distinct cellular programs. The induction of these programs is favored by global transcriptome repression upon stress. Cells displaying basal expression of the osmoresponsive program are hyper-responsive and resistant to stress. Through a transcription-focused analysis of more than 300 RNA-barcoded deletion mutants, we identify genetic factors that shape the heterogeneity of the osmostress-induced transcriptome, define regulators of stress-related subpopulations and find a link between transcriptional heterogeneity and increased cell fitness. Our findings provide a regulatory map of the complex transcriptional phenotypes underlying osmoadaptation in yeast and highlight the importance of transcriptional heterogeneity in generating distinct adaptive strategies.

Expression Dynamics and Genetic Compensation of Cell Cycle Paralogues in Saccharomyces cerevisiae

Cell cycle progression of the yeast Saccharomyces cerevisiae is largely driven by the expression of cyclins, which in turn bind the cyclin-dependent kinase CDK1 providing specificity. Due to the duplication of the yeast genome during evolution, most of the cyclins are present as a pair of paralogues, which are considered to have similar functions and periods of expression. Here, we use single molecule inexpensive fluorescence in situ hybridization (smiFISH) to measure the expression of five pairs of paralogous genes relevant for cell cycle progression (CLN1/CLN2, CLB5/CLB6, CLB3/CLB4, CLB1/CLB2 and ACE2/SWI5) in a large number of unsynchronized single cells representing all cell cycle phases. We systematically compare their expression patterns and strengths. In addition, we also analyze the effect of the knockout of one part of each pair on the expression of the other gene. In order to classify cells into specific cell cycle phases, we developed a convolutional neural network (CNN). We find that the expression levels of some cell-cycle related paralogues differ in their correlation, with CLN1 and CLN2 showing strong correlation and CLB3 and CLB4 showing weakest correlation. The temporal profiles of some pairs also differ. Upon deletion of their paralogue, CLB1 and CLB2 seem to compensate for the expression of the other gene, while this was not observed for ACE2/SWI5. Interestingly, CLB1 and CLB2 also seem to share work between mother and bud in the G2 phase, where CLB2 is primarily expressed in the bud and CLB1 in the mother. Taken together, our results suggest that paralogues related to yeast cell cycle progression should not be considered as the same but differ both in their expression strength and timing as well in their precise role in cell cycle regulation.

Halfpipe: a tool for analyzing metabolic labeling RNA-seq data to quantify RNA half-lives

We introduce Halfpipe, a tool for analyzing RNA-seq data from metabolic RNA labeling experiments. Its main features are the absolute quantification of 4-thiouridine-labeling-induced T>C conversions in the data as generated by SLAM-seq, calculating the proportion of newly synthesized transcripts, and estimating subcellular RNA half-lives. Halfpipe excels at correcting critical biases caused by typically low labeling efficiency. We measure and compare the RNA metabolism in the G1 phase and during the mitosis of synchronized human cells. We find that RNA half-lives of constantly expressed RNAs are similar in mitosis and G1 phase, suggesting that RNA stability of those genes is constant throughout the cell cycle. Our estimates correlate well with literature values and with known RNA sequence features. Halfpipe is freely available at https://github.com/IMSBCompBio/Halfpipe.

mRNA stability fine-tunes gene expression in the developing cortex to control neurogenesis

RNA abundance is controlled by rates of synthesis and degradation. Although mis-regulation of RNA turnover is linked to neurodevelopmental disorders, how it contributes to cortical development is largely unknown. Here, we discover the landscape of RNA stability regulation in the cerebral cortex and demonstrate that intact RNA decay machinery is essential for corticogenesis in vivo. We use SLAM-seq to measure RNA half-lives transcriptome-wide across multiple stages of cortical development. Leveraging these data, we discover cis-acting features associated with RNA stability and probe the relationship between RNA half-life and developmental expression changes. Notably, RNAs that are up-regulated across development tend to be more stable, while down-regulated RNAs are less stable. Using compound mouse genetics, we discover CNOT3, a core component of the CCR4-NOT deadenylase complex linked to neurodevelopmental disease, is essential for cortical development. Conditional knockout of Cnot3 in neural progenitors and their progeny in the developing mouse cortex leads to severe microcephaly due to altered cell fate and p53-dependent apoptosis. Finally, we define the molecular targets of CNOT3, revealing it controls expression of poorly expressed, non-optimal mRNAs in the cortex, including cell cycle-related transcripts. Collectively, our findings demonstrate that fine-tuned control of RNA turnover is crucial for brain development.

RNA Decay Assay: 5-Ethynyl-Uridine Labeling and Chasing

Eukaryotic RNA synthesis and degradation are intricately regulated, impacting on gene expression dynamics. RNA stability varies in individual transcripts and is modulated by trans-acting factors such as microRNAs, long noncoding RNAs, and RNA-binding proteins, which determine protein output and subsequent cellular processes. To measure RNA decay rate, accurate and reliable methodologies are essential in the field of RNA biology. Transcription inhibition and metabolic labeling enable comprehensive investigations on RNA decay, offering critical insights into dynamic regulation of RNA decay. Transcription shut-off has been employed widely by using various approaches, such as treatment with chemical inhibitors or generation of temperature-sensitive mutants of RNA polymerases. However, it has limitations, providing a static view and lacking real-time dynamics as well as precise measurement of decay rate. Metabolic labeling, a method of incorporating modified nucleotides into RNA transcripts, complements shut-off approaches, allowing selective monitoring of newly synthesized RNA and tracing decay intermediates. The purpose of the protocol described in this chapter is to assess the kinetics and statics of newly synthesized RNA and its decay by 5-ethynyl uridine labeling.

Osmotic disruption of chromatin induces Topoisomerase 2 activity at sites of transcriptional stress

Transcription generates superhelical stress in DNA that poses problems for genome stability, but determining when and where such stress arises within chromosomes is challenging. Here, using G1-arrested S. cerevisiae cells, and employing rapid fixation and ultra-sensitive enrichment, we utilise the physiological activity of endogenous topoisomerase 2 (Top2) as a probe of transcription-induced superhelicity. We demonstrate that Top2 activity is surprisingly uncorrelated with transcriptional activity, suggesting that superhelical stress is obscured from Top2 within chromatin in vivo. We test this idea using osmotic perturbation-a treatment that transiently destabilises chromatin in vivo-revealing that Top2 activity redistributes within sub-minute timescales into broad zones patterned by long genes, convergent gene arrays, and transposon elements-and also by acute transcriptional induction. We propose that latent superhelical stress is normally absorbed by the intrinsic topological buffering capacity of chromatin, helping to avoid spurious topoisomerase activity arising within the essential coding regions of the genome.

Modeling of mRNA deadenylation rates reveal a complex relationship between mRNA deadenylation and decay

Complete cytoplasmic polyadenosine tail (polyA-tail) deadenylation is thought to be essential for initiating mRNA decapping and subsequent degradation. To investigate this prevalent model, we conducted direct RNA sequencing of S. cerevisiae mRNAs derived from chase experiments under steady-state and stress condition. Subsequently, we developed a numerical model based on a modified gamma distribution function, which estimated the transcriptomic deadenylation rate at 10 A/min. A simplified independent method, based on the delineation of quantile polyA-tail values, showed a correlation between the decay and deadenylation rates of individual mRNAs, which appeared consistent within functional transcript groups and associated with codon optimality. Notably, these rates varied during the stress response. Detailed analysis of ribosomal protein-coding mRNAs (RPG mRNAs), constituting 40% of the transcriptome, singled out this transcript group. While deadenylation and decay of RPG mRNAs accelerated under heat stress, their degradation could proceed even when deadenylation was blocked, depending entirely on ongoing nuclear export. Our findings support the general primary function of deadenylation in dictating the onset of decapping, while also demonstrating complex relations between these processes.

RNA degradation triggered by decapping is largely independent of initial deadenylation

RNA stability, important for eukaryotic gene expression, is thought to depend on deadenylation rates, with shortened poly(A) tails triggering decapping and 5' to 3' degradation. In contrast to this view, recent large-scale studies indicate that the most unstable mRNAs have, on average, long poly(A) tails. To clarify the role of deadenylation in mRNA decay, we first modeled mRNA poly(A) tail kinetics and mRNA stability in yeast. Independent of deadenylation rates, differences in mRNA decapping rates alone were sufficient to explain current large-scale results. To test the hypothesis that deadenylation and decapping are uncoupled, we used rapid depletion of decapping and deadenylation enzymes and measured changes in mRNA levels, poly(A) length and stability, both transcriptome-wide and with individual reporters. These experiments revealed that perturbations in poly(A) tail length did not correlate with variations in mRNA stability. Thus, while deadenylation may be critical for specific regulatory mechanisms, our results suggest that for most yeast mRNAs, it is not critical for mRNA decapping and degradation.

Unveiling RNA structure-mediated regulations of RNA stability in wheat

Despite the critical role of mRNA stability in post-transcriptional gene regulation, research on this topic in wheat, a vital agricultural crop, remains unclear. Our study investigated the mRNA decay landscape of durum wheat (Triticum turgidum L. ssp. durum, BBAA), revealing subgenomic asymmetry in mRNA stability and its impact on steady-state mRNA abundance. Our findings indicate that the 3' UTR structure and homoeolog preference for RNA structural motifs can influence mRNA stability, leading to subgenomic RNA decay imbalance. Furthermore, single-nucleotide variations (SNVs) selected for RNA structural motifs during domestication can cause variations in subgenomic mRNA stability and subsequent changes in steady-state expression levels. Our research on the transcriptome stability of polyploid wheat highlights the regulatory role of non-coding region structures in mRNA stability, and how domestication shaped RNA structure, altering subgenomic mRNA stability. These results illustrate the importance of RNA structure-mediated post-transcriptional gene regulation in wheat and pave the way for its potential use in crop improvement.

Dynamic changes in mRNA nucleocytoplasmic localization in the nitrate response of Arabidopsis roots

Nitrate is a nutrient and signal that regulates gene expression. The nitrate response has been extensively characterized at the organism, organ, and cell-type-specific levels, but intracellular mRNA dynamics remain unexplored. To characterize nuclear and cytoplasmic transcriptome dynamics in response to nitrate, we performed a time-course expression analysis after nitrate treatment in isolated nuclei, cytoplasm, and whole roots. We identified 402 differentially localized transcripts (DLTs) in response to nitrate treatment. Induced DLT genes showed rapid and transient recruitment of the RNA polymerase II, together with an increase in the mRNA turnover rates. DLTs code for genes involved in metabolic processes, localization, and response to stimulus indicating DLTs include genes with relevant functions for the nitrate response that have not been previously identified. Using single-molecule RNA FISH, we observed early nuclear accumulation of the NITRATE REDUCTASE 1 (NIA1) transcripts in their transcription sites. We found that transcription of NIA1, a gene showing delayed cytoplasmic accumulation, is rapidly and transiently activated; however, its transcripts become unstable when they reach the cytoplasm. Our study reveals the dynamic localization of mRNAs between the nucleus and cytoplasm as an emerging feature in the temporal control of gene expression in response to nitrate treatment in Arabidopsis roots.

Multiple direct and indirect roles of the Paf1 complex in transcription elongation, splicing, and histone modifications

The polymerase-associated factor 1 (Paf1) complex (Paf1C) is a conserved protein complex with critical functions during eukaryotic transcription. Previous studies showed that Paf1C is multi-functional, controlling specific aspects of transcription ranging from RNA polymerase II (RNAPII) processivity to histone modifications. However, it is unclear how specific Paf1C subunits directly impact transcription and coupled processes. We have compared conditional depletion to steady-state deletion for each Paf1C subunit to determine the direct and indirect contributions to gene expression in Saccharomyces cerevisiae. Using nascent transcript sequencing, RNAPII profiling, and modeling of transcription elongation dynamics, we have demonstrated direct effects of Paf1C subunits on RNAPII processivity and elongation rate and indirect effects on transcript splicing and repression of antisense transcripts. Further, our results suggest that the direct transcriptional effects of Paf1C cannot be readily assigned to any particular histone modification. This work comprehensively analyzes both the immediate and the extended roles of each Paf1C subunit in transcription elongation and transcript regulation.

Transcriptional silencing in Saccharomyces cerevisiae: known unknowns

Transcriptional silencing in Saccharomyces cerevisiae is a persistent and highly stable form of gene repression. It involves DNA silencers and repressor proteins that bind nucleosomes. The silenced state is influenced by numerous factors including the concentration of repressors, nature of activators, architecture of regulatory elements, modifying enzymes and the dynamics of chromatin.Silencers function to increase the residence time of repressor Sir proteins at silenced domains while clustering of silenced domains enables increased concentrations of repressors and helps facilitate long-range interactions. The presence of an accessible NDR at the regulatory regions of silenced genes, the cycling of chromatin configurations at regulatory sites, the mobility of Sir proteins, and the non-uniform distribution of the Sir proteins across the silenced domain, all result in silenced chromatin that only stably silences weak promoters and enhancers via changes in transcription burst duration and frequency.These data collectively suggest that silencing is probabilistic and the robustness of silencing is achieved through sub-optimization of many different nodes of action such that a stable expression state is generated and maintained even though individual constituents are in constant flux.

Dissecting key regulators of transcriptome kinetics through scalable single-cell RNA profiling of pooled CRISPR screens

We present a combinatorial indexing method, PerturbSci-Kinetics, for capturing whole transcriptomes, nascent transcriptomes and single guide RNA (sgRNA) identities across hundreds of genetic perturbations at the single-cell level. Profiling a pooled CRISPR screen targeting various biological processes, we show the gene expression regulation during RNA synthesis, processing and degradation, miRNA biogenesis and mitochondrial mRNA processing, systematically decoding the genome-wide regulatory network that underlies RNA temporal dynamics at scale.

Nuclear export is a limiting factor in eukaryotic mRNA metabolism

The eukaryotic mRNA life cycle includes transcription, nuclear mRNA export and degradation. To quantify all these processes simultaneously, we perform thiol-linked alkylation after metabolic labeling of RNA with 4-thiouridine (4sU), followed by sequencing of RNA (SLAM-seq) in the nuclear and cytosolic compartments of human cancer cells. We develop a model that reliably quantifies mRNA-specific synthesis, nuclear export, and nuclear and cytosolic degradation rates on a genome-wide scale. We find that nuclear degradation of polyadenylated mRNA is negligible and nuclear mRNA export is slow, while cytosolic mRNA degradation is comparatively fast. Consequently, an mRNA molecule generally spends most of its life in the nucleus. We also observe large differences in the nuclear export rates of different 3'UTR transcript isoforms. Furthermore, we identify genes whose expression is abruptly induced upon metabolic labeling. These transcripts are exported substantially faster than average mRNAs, suggesting the existence of alternative export pathways. Our results highlight nuclear mRNA export as a limiting factor in mRNA metabolism and gene regulation.

Genome-scale chromatin binding dynamics of RNA Polymerase II general transcription machinery components

A great deal of work has revealed, in structural detail, the components of the preinitiation complex (PIC) machinery required for initiation of mRNA gene transcription by RNA polymerase II (Pol II). However, less-well understood are the in vivo PIC assembly pathways and their kinetics, an understanding of which is vital for determining how rates of in vivo RNA synthesis are established. We used competition ChIP in budding yeast to obtain genome-scale estimates of the residence times for five general transcription factors (GTFs): TBP, TFIIA, TFIIB, TFIIE and TFIIF. While many GTF-chromatin interactions were short-lived ( < 1 min), there were numerous interactions with residence times in the range of several minutes. Sets of genes with a shared function also shared similar patterns of GTF kinetic behavior. TFIIE, a GTF that enters the PIC late in the assembly process, had residence times correlated with RNA synthesis rates. The datasets and results reported here provide kinetic information for most of the Pol II-driven genes in this organism, offering a rich resource for exploring the mechanistic relationships between PIC assembly, gene regulation, and transcription.

Multiple direct and indirect roles of Paf1C in elongation, splicing, and histone post-translational modifications

Paf1C is a highly conserved protein complex with critical functions during eukaryotic transcription. Previous studies have shown that Paf1C is multi-functional, controlling specific aspects of transcription, ranging from RNAPII processivity to histone modifications. However, it is unclear how specific Paf1C subunits directly impact transcription and coupled processes. We have compared conditional depletion to steady-state deletion for each Paf1C subunit to determine the direct and indirect contributions to gene expression in Saccharomyces cerevisiae. Using nascent transcript sequencing, RNAPII profiling, and modeling of transcription elongation dynamics, we have demonstrated direct effects of Paf1C subunits on RNAPII processivity and elongation rate and indirect effects on transcript splicing and repression of antisense transcripts. Further, our results suggest that the direct transcriptional effects of Paf1C cannot be readily assigned to any particular histone modification. This work comprehensively analyzes both the immediate and extended roles of each Paf1C subunit in transcription elongation and transcript regulation.

Yeast heterochromatin stably silences only weak regulatory elements by altering burst duration

Transcriptional silencing in Saccharomyces cerevisiae involves the generation of a chromatin state that stably represses transcription. Using multiple reporter assays, a diverse set of upstream activating sequence enhancers and core promoters were investigated for their susceptibility to silencing. We show that heterochromatin stably silences only weak and stress-induced regulatory elements but is unable to stably repress housekeeping gene regulatory elements, and the partial repression of these elements did not result in bistable expression states. Permutation analysis of enhancers and promoters indicates that both elements are targets of repression. Chromatin remodelers help specific regulatory elements to resist repression, most probably by altering nucleosome mobility and changing transcription burst duration. The strong enhancers/promoters can be repressed if silencer-bound Sir1 is increased. Together, our data suggest that the heterochromatic locus has been optimized to stably silence the weak mating-type gene regulatory elements but not strong housekeeping gene regulatory sequences.

Size fractionated NET-Seq reveals a conserved architecture of transcription units around yeast genes

Genomes from yeast to humans are subject to pervasive transcription. A single round of pervasive transcription is sufficient to alter local chromatin conformation, nucleosome dynamics and gene expression, but is hard to distinguish from background signals. Size fractionated native elongating transcript sequencing (sfNET-Seq) was developed to precisely map nascent transcripts independent of expression levels. RNAPII-associated nascent transcripts are fractionation into different size ranges before library construction. When anchored to the transcription start sites (TSS) of annotated genes, the combined pattern of the output metagenes gives the expected reference pattern. Bioinformatic pattern matching to the reference pattern identified 9542 transcription units in Saccharomyces cerevisiae, of which 47% are coding and 53% are noncoding. In total, 3113 (33%) are unannotated noncoding transcription units. Anchoring all transcription units to the TSS or polyadenylation site (PAS) of annotated genes reveals distinctive architectures of linked pairs of divergent transcripts approximately 200nt apart. The Reb1 transcription factor is enriched 30nt downstream of the PAS only when an upstream (TSS -60nt with respect to PAS) noncoding transcription unit co-occurs with a downstream (TSS +150nt) coding transcription unit and acts to limit levels of upstream antisense transcripts. The potential for extensive transcriptional interference is evident from low abundance unannotated transcription units with variable TSS (median -240nt) initiating within a 500nt window upstream of, and transcribing over, the promoters of protein-coding genes. This study confirms a highly interleaved yeast genome with different types of transcription units altering the chromatin landscape in distinctive ways, with the potential to exert extensive regulatory control.

Broad variation in response of individual introns to splicing inhibitors in a humanized yeast strain

Intron branchpoint (BP) recognition by the U2 snRNP is a critical step of splicing, vulnerable to recurrent cancer mutations and bacterial natural product inhibitors. The BP binds a conserved pocket in the SF3B1 (human) or Hsh155 (yeast) U2 snRNP protein. Amino acids that line this pocket affect the binding of splicing inhibitors like Pladienolide-B (Plad-B), such that organisms differ in their sensitivity. To study the mechanism of splicing inhibitor action in a simplified system, we modified the naturally Plad-B resistant yeast Saccharomyces cerevisiae by changing 14 amino acids in the Hsh155 BP pocket to those from human. This humanized yeast grows normally, and splicing is largely unaffected by the mutation. Splicing is inhibited within minutes after the addition of Plad-B, and different introns appear inhibited to different extents. Intron-specific inhibition differences are also observed during cotranscriptional splicing in Plad-B using single-molecule intron tracking to minimize gene-specific transcription and decay rates that cloud estimates of inhibition by standard RNA-seq. Comparison of Plad-B intron sensitivities to those of the structurally distinct inhibitor Thailanstatin-A reveals intron-specific differences in sensitivity to different compounds. This work exposes a complex relationship between the binding of different members of this class of inhibitors to the spliceosome and intron-specific rates of BP recognition and catalysis. Introns with variant BP sequences seem particularly sensitive, echoing observations from mammalian cells, where monitoring individual introns is complicated by multi-intron gene architecture and alternative splicing. The compact yeast system may hasten the characterization of splicing inhibitors, accelerating improvements in selectivity and therapeutic efficacy.

Late consolidation of rRNA structure during co-transcriptional assembly in E. coli by time-resolved DMS footprinting

The production of new ribosomes requires proper folding of the rRNA and the addition of more than 50 ribosomal proteins. The structures of some assembly intermediates have been determined by cryo-electron microscopy, yet these structures do not provide information on the folding dynamics of the rRNA. To visualize the changes in rRNA structure during ribosome assembly in E. coli cells, transcripts were pulse-labeled with 4-thiouridine and the structure of newly made rRNA probed at various times by dimethyl sulfate modification and mutational profiling sequencing (4U-DMS-MaPseq). The in-cell DMS modification patterns revealed that many long-range rRNA tertiary interactions and protein binding sites through the 16S and 23S rRNA remain partially unfolded 1.5 min after transcription. By contrast, the active sites were continually shielded from DMS modification, suggesting that these critical regions are guarded by cellular factors throughout assembly. Later, bases near the peptidyl tRNA site exhibited specific rearrangements consistent with the binding and release of assembly factors. Time-dependent structure-probing in cells suggests that many tertiary interactions throughout the new ribosomal subunits remain mobile or unfolded until the late stages of subunit maturation.

Transcriptome-Wide Analysis of mRNA Adenylation Status in Yeast Using Nanopore Sequencing

There are multiple methods for studying deadenylation, either in vitro or in vivo, which allow for observation of mRNA abundance or poly(A) tail dynamics. However, direct RNA sequencing using the Oxford Nanopore Technologies (ONT) platform makes it possible to conduct transcriptome-wide analyses at the single-molecule level without the PCR bias introduced by other methods. In this chapter, we provide a protocol to measure both RNA levels and poly(A)-tail lengths in the yeast Saccharomyces cerevisiae using ONT.

High-resolution temporal profiling of E. coli transcriptional response

Understanding how cells dynamically adapt to their environment is a primary focus of biology research. Temporal information about cellular behavior is often limited by both small numbers of data time-points and the methods used to analyze this data. Here, we apply unsupervised machine learning to a data set containing the activity of 1805 native promoters in E. coli measured every 10 minutes in a high-throughput microfluidic device via fluorescence time-lapse microscopy. Specifically, this data set reveals E. coli transcriptome dynamics when exposed to different heavy metal ions. We use a bioinformatics pipeline based on Independent Component Analysis (ICA) to generate insights and hypotheses from this data. We discovered three primary, time-dependent stages of promoter activation to heavy metal stress (fast, intermediate, and steady). Furthermore, we uncovered a global strategy E. coli uses to reallocate resources from stress-related promoters to growth-related promoters following exposure to heavy metal stress.

Broad variation in response of individual introns to splicing inhibitors in a humanized yeast strain

Intron branch point (BP) recognition by the U2 snRNP is a critical step of splicing, vulnerable to recurrent cancer mutations and bacterial natural product inhibitors. The BP binds a conserved pocket in the SF3B1 (human) or Hsh155 (yeast) U2 snRNP protein. Amino acids that line this pocket affect binding of splicing inhibitors like Pladienolide-B (Plad-B), such that organisms differ in their sensitivity. To study the mechanism of splicing inhibitor action in a simplified system, we modified the naturally Plad-B resistant yeast Saccharomyces cerevisiae by changing 14 amino acids in the Hsh155 BP pocket to those from human. This humanized yeast grows normally, and splicing is largely unaffected by the mutation. Splicing is inhibited within minutes after addition of Plad-B, and different introns appear inhibited to different extents. Intron-specific inhibition differences are also observed during co-transcriptional splicing in Plad-B using single-molecule intron tracking (SMIT) to minimize gene-specific transcription and decay rates that cloud estimates of inhibition by standard RNA-seq. Comparison of Plad-B intron sensitivities to those of the structurally distinct inhibitor Thailanstatin-A reveals intron-specific differences in sensitivity to different compounds. This work exposes a complex relationship between binding of different members of this class of inhibitors to the spliceosome and intron-specific rates of BP recognition and catalysis. Introns with variant BP sequences seem particularly sensitive, echoing observations from mammalian cells, where monitoring individual introns is complicated by multi-intron gene architecture and alternative splicing. The compact yeast system may hasten characterization of splicing inhibitors, accelerating improvements in selectivity and therapeutic efficacy.

Yeast Heterochromatin Only Stably Silences Weak Regulatory Elements by Altering Burst Duration

The interplay between nucleosomes and transcription factors leads to programs of gene expression. Transcriptional silencing involves the generation of a chromatin state that represses transcription and is faithfully propagated through DNA replication and cell division. Using multiple reporter assays, including directly visualizing transcription in single cells, we investigated a diverse set of UAS enhancers and core promoters for their susceptibility to heterochromatic gene silencing. These results show that heterochromatin only stably silences weak and stress induced regulatory elements but is unable to stably repress housekeeping gene regulatory elements and the partial repression did not result in bistable expression states. Permutation analysis of different UAS enhancers and core promoters indicate that both elements function together to determine the susceptibility of regulatory sequences to repression. Specific histone modifiers and chromatin remodellers function in an enhancer specific manner to aid these elements to resist repression suggesting that Sir proteins likely function in part by reducing nucleosome mobility. We also show that the strong housekeeping regulatory elements can be repressed if silencer bound Sir1 is increased, suggesting that Sir1 is a limiting component in silencing. Together, our data suggest that the heterochromatic locus has been optimized to stably silence the weak mating type gene regulatory elements but not strong housekeeping gene regulatory sequences which could help explain why these genes are often found at the boundaries of silenced domains.

SLAM-Drop-seq reveals mRNA kinetic rates throughout the cell cycle

RNA abundance is tightly regulated in eukaryotic cells by modulating the kinetic rates of RNA production, processing, and degradation. To date, little is known about time‐dependent kinetic rates during dynamic processes. Here, we present SLAM‐Drop‐seq, a method that combines RNA metabolic labeling and alkylation of modified nucleotides in methanol‐fixed cells with droplet‐based sequencing to detect newly synthesized and preexisting mRNAs in single cells. As a first application, we sequenced 7280 HEK293 cells and calculated gene‐specific kinetic rates during the cell cycle using the novel package Eskrate. Of the 377 robust‐cycling genes that we identified, only a minor fraction is regulated solely by either dynamic transcription or degradation (6 and 4%, respectively). By contrast, the vast majority (89%) exhibit dynamically regulated transcription and degradation rates during the cell cycle. Our study thus shows that temporally regulated mRNA degradation is fundamental for the correct expression of a majority of cycling genes. SLAM‐Drop‐seq, combined with Eskrate, is a powerful approach to understanding the underlying mRNA kinetics of single‐cell gene expression dynamics in continuous biological processes.

Polysome propensity and tunable thresholds in coding sequence length enable differential mRNA stability

The half-life of mRNAs, as well as their translation, increases in proportion to the optimal codons, indicating a tight coupling of codon-dependent differential translation and degradation. Little is known about the regulation of this coupling. We found that the mRNA stability gain in yeast depends on the mRNA coding sequence length. Below a critical length, codon optimality fails to affect the stability of mRNAs although they can be efficiently translated into short peptides and proteins. Above this threshold length, codon optimality-dependent differential mRNA stability emerges in a switch-like fashion, which coincides with a similar increase in the polysome propensity of the mRNAs. This threshold length can be tuned by the untranslated regions (UTR). Some of these UTRs can destabilize mRNAs without reducing translation, which plays a role in controlling the amplitude of the oscillatory expression of cell cycle genes. Our findings help understand the translation of short peptides from noncoding RNAs and the translation by localized monosomes in neurons.

Simultaneous estimation of gene regulatory network structure and RNA kinetics from single cell gene expression

Cells respond to environmental and developmental stimuli by remodeling their transcriptomes through regulation of both mRNA transcription and mRNA decay. A central goal of biology is identifying the global set of regulatory relationships between factors that control mRNA production and degradation and their target transcripts and construct a predictive model of gene expression. Regulatory relationships are typically identified using transcriptome measurements and causal inference algorithms. RNA kinetic parameters are determined experimentally by employing run-on or metabolic labeling (e.g. 4-thiouracil) methods that allow transcription and decay rates to be separately measured. Here, we develop a deep learning model, trained with single-cell RNA-seq data, that both infers causal regulatory relationships and estimates RNA kinetic parameters. The resulting in silico model predicts future gene expression states and can be perturbed to simulate the effect of transcription factor changes. We acquired model training data by sequencing the transcriptomes of 175,000 individual Saccharomyces cerevisiae cells that were subject to an external perturbation and continuously sampled over a one hour period. The rate of change for each transcript was calculated on a per-cell basis to estimate RNA velocity. We then trained a deep learning model with transcriptome and RNA velocity data to calculate time-dependent estimates of mRNA production and decay rates. By separating RNA velocity into transcription and decay rates, we show that rapamycin treatment causes existing ribosomal protein transcripts to be rapidly destabilized, while production of new transcripts gradually slows over the course of an hour. The neural network framework we present is designed to explicitly model causal regulatory relationships between transcription factors and their genes, and shows superior performance to existing models on the basis of recovery of known regulatory relationships. We validated the predictive power of the model by perturbing transcription factors in silico and comparing transcriptome-wide effects with experimental data. Our study represents the first step in constructing a complete, predictive, biophysical model of gene expression regulation.

Dominant constraints on the evolution of rhythmic gene expression

Although the individual transcriptional regulators of the core circadian clock are distinct among different organisms, the autoregulatory feedback loops they form are conserved. This unified design principle explains how daily physiological activities oscillate across species. However, it is unknown whether analogous design principles govern the gene expression output of circadian clocks. In this study, we performed a comparative analysis of rhythmic gene expression in eight diverse species and identified four common distribution patterns of cycling gene expression across these species. We hypothesized that the maintenance of reduced energetic costs constrains the evolution of rhythmic gene expression. Our large-scale computational simulations support this hypothesis by showing that selection against high-energy expenditure completely regenerates all cycling gene patterns. Moreover, we find that the peaks of rhythmic expression have been subjected to this type of selective pressure. The results suggest that selective pressure from circadian regulation efficiently removes unnecessary gene products from the transcriptome, thereby significantly impacting its evolutionary path.

The mRNA stability factor Khd4 defines a specific mRNA regulon for membrane trafficking in the pathogen Ustilago maydis

Fungal pathogens depend on sophisticated gene expression programs for successful infection. A crucial component is RNA regulation mediated by RNA-binding proteins (RBPs). However, little is known about the spatiotemporal RNA control mechanisms during fungal pathogenicity. Here, we discover that the RBP Khd4 defines a distinct mRNA regulon to orchestrate membrane trafficking during pathogenic development of Ustilago maydis. By establishing hyperTRIBE for fungal RBPs, we generated a comprehensive transcriptome-wide map of Khd4 interactions in vivo. We identify a defined set of target mRNAs enriched for regulatory proteins involved, e.g., in GTPase signaling. Khd4 controls the stability of target mRNAs via its cognate regulatory element AUACCC present in their 3' untranslated regions. Studying individual examples reveals a unique link between Khd4 and vacuole maturation. Thus, we uncover a distinct role for an RNA stability factor defining a specific mRNA regulon for membrane trafficking during pathogenicity.

Advances in S. cerevisiae Engineering for Xylose Fermentation and Biofuel Production: Balancing Growth, Metabolism, and Defense

Genetically engineering microorganisms to produce chemicals has changed the industrialized world. The budding yeast Saccharomyces cerevisiae is frequently used in industry due to its genetic tractability and unique metabolic capabilities. S. cerevisiae has been engineered to produce novel compounds from diverse sugars found in lignocellulosic biomass, including pentose sugars, like xylose, not recognized by the organism. Engineering high flux toward novel compounds has proved to be more challenging than anticipated since simply introducing pathway components is often not enough. Several studies show that the rewiring of upstream signaling is required to direct products toward pathways of interest, but doing so can diminish stress tolerance, which is important in industrial conditions. As an example of these challenges, we reviewed S. cerevisiae engineering efforts, enabling anaerobic xylose fermentation as a model system and showcasing the regulatory interplay's controlling growth, metabolism, and stress defense. Enabling xylose fermentation in S. cerevisiae requires the introduction of several key metabolic enzymes but also regulatory rewiring of three signaling pathways at the intersection of the growth and stress defense responses: the RAS/PKA, Snf1, and high osmolarity glycerol (HOG) pathways. The current studies reviewed here suggest the modulation of global signaling pathways should be adopted into biorefinery microbial engineering pipelines to increase efficient product yields.

Genome-scale chromatin interaction dynamic measurements for key components of the RNA Pol II general transcription machinery

Background

A great deal of work has revealed in structural detail the components of the machinery responsible for mRNA gene transcription initiation. These include the general transcription factors (GTFs), which assemble at promoters along with RNA Polymerase II (Pol II) to form a preinitiation complex (PIC) aided by the activities of cofactors and site-specific transcription factors (TFs). However, less well understood are the in vivo PIC assembly pathways and their kinetics, an understanding of which is vital for determining on a mechanistic level how rates of in vivo RNA synthesis are established and how cofactors and TFs impact them.

Results

We used competition ChIP to obtain genome-scale estimates of the residence times for five GTFs: TBP, TFIIA, TFIIB, TFIIE and TFIIF in budding yeast. While many GTF-chromatin interactions were short-lived (< 1 min), there were numerous interactions with residence times in the several minutes range. Sets of genes with a shared function also shared similar patterns of GTF kinetic behavior. TFIIE, a GTF that enters the PIC late in the assembly process, had residence times correlated with RNA synthesis rates.

Conclusions

The datasets and results reported here provide kinetic information for most of the Pol II-driven genes in this organism and therefore offer a rich resource for exploring the mechanistic relationships between PIC assembly, gene regulation, and transcription. The relationships between gene function and GTF dynamics suggest that shared sets of TFs tune PIC assembly kinetics to ensure appropriate levels of expression.

Dynamically regulated transcription factors are encoded by highly unstable mRNAs in the Drosophila larval brain

The level of each RNA species depends on the balance between its rates of production and decay. Although previous studies have measured RNA decay across the genome in tissue culture and single-celled organisms, few experiments have been performed in intact complex tissues and organs. It is therefore unclear whether the determinants of RNA decay found in cultured cells are preserved in an intact tissue, and whether they differ between neighboring cell types and are regulated during development. To address these questions, we measured RNA synthesis and decay rates genome wide via metabolic labeling of whole cultured Drosophila larval brains using 4-thiouridine. Our analysis revealed that decay rates span a range of more than 100-fold, and that RNA stability is linked to gene function, with mRNAs encoding transcription factors being much less stable than mRNAs involved in core metabolic functions. Surprisingly, among transcription factor mRNAs there was a clear demarcation between more widely used transcription factors and those that are expressed only transiently during development. mRNAs encoding transient transcription factors are among the least stable in the brain. These mRNAs are characterized by epigenetic silencing in most cell types, as shown by their enrichment with the histone modification H3K27me3. Our data suggest the presence of an mRNA destabilizing mechanism targeted to these transiently expressed transcription factors to allow their levels to be regulated rapidly with high precision. Our study also demonstrates a general method for measuring mRNA transcription and decay rates in intact organs or tissues, offering insights into the role of mRNA stability in the regulation of complex developmental programs.

Functional analysis of a random-sequence chromosome reveals a high level and the molecular nature of transcriptional noise in yeast cells

We measure transcriptional noise in yeast by analyzing chromatin structure and transcription of an 18-kb region of DNA whose sequence was randomly generated. Nucleosomes fully occupy random-sequence DNA, but nucleosome-depleted regions (NDRs) are much less frequent, and there are fewer well-positioned nucleosomes and shorter nucleosome arrays. Steady-state levels of random-sequence RNAs are comparable to yeast mRNAs, although transcription and decay rates are higher. Transcriptional initiation from random-sequence DNA occurs at numerous sites, indicating very low intrinsic specificity of the RNA Pol II machinery. In contrast, poly(A) profiles of random-sequence RNAs are roughly comparable to those of yeast mRNAs, suggesting limited evolutionary restraints on poly(A) site choice. Random-sequence RNAs show higher cell-to-cell variability than yeast mRNAs, suggesting that functional elements limit variability. These observations indicate that transcriptional noise occurs at high levels in yeast, and they provide insight into how chromatin and transcription patterns arise from the evolved yeast genome.

SLAM-seq reveals early transcriptomic response mechanisms upon glutamine deprivation in Chinese hamster ovary cells

Mammalian cells frequently encounter subtle perturbations during recombinant protein production. Identifying the genetic factors that govern the cellular stress response can facilitate targeted genetic engineering to obtain production cell lines that demonstrate a higher stress tolerance. To simulate nutrient stress, Chinese hamster ovary (CHO) cells were transferred into a glutamine(Q)-free medium and transcriptional dynamics using thiol(SH)-linked alkylation for the metabolic sequencing of RNA (SLAM-seq) along with standard RNA-seq of stressed and unstressed cells were investigated. The SLAM-seq method allows differentiation between actively transcribed, nascent mRNA, and total (previously present) mRNA in the sample, adding an additional, time-resolved layer to classic RNA-sequencing. The cells tackle amino acid (AA) limitation by inducing the integrated stress response (ISR) signaling pathway, reflected in Atf4 overexpression in the early hours post Q deprivation, leading to subsequent activation of its targets, Asns, Atf3, Ddit3, Eif4ebp1, Gpt2, Herpud1, Slc7a1, Slc7a11, Slc38a2, Trib3, and Vegfa. The GCN2-eIF2α-ATF4 pathway is confirmed by a significant halt in transcription of translation-related genes at 24 h post Q deprivation. The downregulation of lipid synthesis indicates the inhibition of the mTOR pathway, further confirmed by overexpression of Sesn2. Furthermore, SLAM-seq detects short-lived transcription factors, such as Egr1, that would have been missed in standard experimental designs with RNA-seq. Our results describe the successful establishment of SLAM-seq in CHO cells and therefore facilitate its future use in other scenarios where dynamic transcriptome profiling in CHO cells is essential.

Determining RNA Natural Modifications and Nucleoside Analog-Labeled Sites by a Chemical/Enzyme-Induced Base Mutation Principle

The natural chemical modifications of messenger RNA (mRNA) in living organisms have shown essential roles in both physiology and pathology. The mapping of mRNA modifications is critical for interpreting their biological functions. In another dimension, the synthesized nucleoside analogs can enable chemical labeling of cellular mRNA through a metabolic pathway, which facilitates the study of RNA dynamics in a pulse-chase manner. In this regard, the sequencing tools for mapping both natural modifications and nucleoside tags on mRNA at single base resolution are highly necessary. In this work, we review the progress of chemical sequencing technology for determining both a variety of naturally occurring base modifications mainly on mRNA and a few on transfer RNA and metabolically incorporated artificial base analogs on mRNA, and further discuss the problems and prospects in the field.

Performing in spite of starvation: How Saccharomyces cerevisiae maintains robust growth when facing famine zones in industrial bioreactors

In fed-batch operated industrial bioreactors, glucose-limited feeding is commonly applied for optimal control of cell growth and product formation. Still, microbial cells such as yeasts and bacteria are frequently exposed to glucose starvation conditions in poorly mixed zones or far away from the feedstock inlet point. Despite its commonness, studies mimicking related stimuli are still underrepresented in scale-up/scale-down considerations. This may surprise as the transition from glucose limitation to starvation has the potential to provoke regulatory responses with negative consequences for production performance. In order to shed more light, we performed gene-expression analysis of Saccharomyces cerevisiae grown in intermittently fed chemostat cultures to study the effect of limitation-starvation transitions. The resulting glucose concentration gradient was representative for the commercial scale and compelled cells to tolerate about 76 s with sub-optimal substrate supply. Special attention was paid to the adaptation status of the population by discriminating between first time and repeated entry into the starvation regime. Unprepared cells reacted with a transiently reduced growth rate governed by the general stress response. Yeasts adapted to the dynamic environment by increasing internal growth capacities at the cost of rising maintenance demands by 2.7%. Evidence was found that multiple protein kinase A (PKA) and Snf1-mediated regulatory circuits were initiated and ramped down still keeping the cells in an adapted trade-off between growth optimization and down-regulation of stress response. From this finding, primary engineering guidelines are deduced to optimize both the production host's genetic background and the design of scale-down experiments.

The genetic and biochemical determinants of mRNA degradation rates in mammals

BACKGROUND

Degradation rate is a fundamental aspect of mRNA metabolism, and the factors governing it remain poorly characterized. Understanding the genetic and biochemical determinants of mRNA half-life would enable more precise identification of variants that perturb gene expression through post-transcriptional gene regulatory mechanisms.

RESULTS

We establish a compendium of 39 human and 27 mouse transcriptome-wide mRNA decay rate datasets. A meta-analysis of these data identified a prevalence of technical noise and measurement bias, induced partially by the underlying experimental strategy. Correcting for these biases allowed us to derive more precise, consensus measurements of half-life which exhibit enhanced consistency between species. We trained substantially improved statistical models based upon genetic and biochemical features to better predict half-life and characterize the factors molding it. Our state-of-the-art model, Saluki, is a hybrid convolutional and recurrent deep neural network which relies only upon an mRNA sequence annotated with coding frame and splice sites to predict half-life (r=0.77). The key novel principle learned by Saluki is that the spatial positioning of splice sites, codons, and RNA-binding motifs within an mRNA is strongly associated with mRNA half-life. Saluki predicts the impact of RNA sequences and genetic mutations therein on mRNA stability, in agreement with functional measurements derived from massively parallel reporter assays.

CONCLUSIONS

Our work produces a more robust ground truth for transcriptome-wide mRNA half-lives in mammalian cells. Using these revised measurements, we trained Saluki, a model that is over 50% more accurate in predicting half-life from sequence than existing models. Saluki succinctly captures many of the known determinants of mRNA half-life and can be rapidly deployed to predict the functional consequences of arbitrary mutations in the transcriptome.

Sublinear scaling of the cellular proteome with ploidy

Ploidy changes are frequent in nature and contribute to evolution, functional specialization and tumorigenesis. Analysis of model organisms of different ploidies revealed that increased ploidy leads to an increase in cell and nuclear volume, reduced proliferation, metabolic changes, lower fitness, and increased genomic instability, but the underlying mechanisms remain poorly understood. To investigate how gene expression changes with cellular ploidy, we analyzed isogenic series of budding yeasts from 1N to 4N. We show that mRNA and protein abundance scales allometrically with ploidy, with tetraploid cells showing only threefold increase in protein abundance compared to haploids. This ploidy-dependent sublinear scaling occurs via decreased rRNA and ribosomal protein abundance and reduced translation. We demonstrate that the activity of Tor1 is reduced with increasing ploidy, which leads to diminished rRNA gene repression via a Tor1-Sch9-Tup1 signaling pathway. mTORC1 and S6K activity are also reduced in human tetraploid cells and the concomitant increase of the Tup1 homolog Tle1 downregulates the rDNA transcription. Our results suggest that the mTORC1-Sch9/S6K-Tup1/TLE1 pathway ensures proteome remodeling in response to increased ploidy.

Quantifying how post-transcriptional noise and gene copy number variation bias transcriptional parameter inference from mRNA distributions

Transcriptional rates are often estimated by fitting the distribution of mature mRNA numbers measured using smFISH (single molecule fluorescence in situ hybridization) with the distribution predicted by the telegraph model of gene expression, which defines two promoter states of activity and inactivity. However, fluctuations in mature mRNA numbers are strongly affected by processes downstream of transcription. In addition, the telegraph model assumes one gene copy but in experiments, cells may have two gene copies as cells replicate their genome during the cell cycle. While it is often presumed that post-transcriptional noise and gene copy number variation affect transcriptional parameter estimation, the size of the error introduced remains unclear. To address this issue, here we measure both mature and nascent mRNA distributions of GAL10 in yeast cells using smFISH and classify each cell according to its cell cycle phase. We infer transcriptional parameters from mature and nascent mRNA distributions, with and without accounting for cell cycle phase and compare the results to live-cell transcription measurements of the same gene. We find that: (i) correcting for cell cycle dynamics decreases the promoter switching rates and the initiation rate, and increases the fraction of time spent in the active state, as well as the burst size; (ii) additional correction for post-transcriptional noise leads to further increases in the burst size and to a large reduction in the errors in parameter estimation. Furthermore, we outline how to correctly adjust for measurement noise in smFISH due to uncertainty in transcription site localisation when introns cannot be labelled. Simulations with parameters estimated from nascent smFISH data, which is corrected for cell cycle phases and measurement noise, leads to autocorrelation functions that agree with those obtained from live-cell imaging.

Yeast osmoregulation - glycerol still in pole position

In response to osmotic dehydration cells sense, signal, alter gene expression, and metabolically counterbalance osmotic differences. The main compatible solute/osmolyte that accumulates in yeast cells is glycerol, which is produced from the glycolytic intermediate dihydroxyacetone phosphate. This review covers recent advancements in understanding mechanisms involved in sensing, signaling, cell-cycle delays, transcriptional responses as well as post-translational modifications on key proteins in osmoregulation. The protein kinase Hog1 is a key-player in many of these events, however, there is also a growing body of evidence for important Hog1-independent mechanisms playing vital roles. Several missing links in our understanding of osmoregulation will be discussed and future avenues for research proposed. The review highlights that this rather simple experimental system—salt/sorbitol and yeast—has developed into an enormously potent model system unravelling important fundamental aspects in biology.

Global SLAM-seq for accurate mRNA decay determination and identification of NMD targets

Gene expression analysis requires accurate measurements of global RNA degradation rates, earlier problematic with methods disruptive to cell physiology. Recently, metabolic RNA labeling emerged as an efficient and minimally invasive technique applied in mammalian cells. Here, we have adapted SH-linked alkylation for the metabolic sequencing of RNA (SLAM-seq) for a global mRNA stability study in yeast using 4-thiouracil pulse-chase labeling. We assign high-confidence half-life estimates for 67.5% of expressed ORFs, and measure a median half-life of 9.4 min. For mRNAs where half-life estimates exist in the literature, their ranking order was in good agreement with previous data, indicating that SLAM-seq efficiently classifies stable and unstable transcripts. We then leveraged our yeast protocol to identify targets of the nonsense-mediated decay (NMD) pathway by measuring the change in RNA half-lives, instead of steady-state RNA level changes. With SLAM-seq, we assign 580 transcripts as putative NMD targets, based on their measured half-lives in wild-type and upf3Δ mutants. We find 225 novel targets, and observe a strong agreement with previous reports of NMD targets, 61.2% of our candidates being identified in previous studies. This indicates that SLAM-seq is a simpler and more economic method for global quantification of mRNA half-lives. Our adaptation for yeast yielded global quantitative measures of the NMD effect on transcript half-lives, high correlation with RNA half-lives measured previously with more technically challenging protocols, and identification of novel NMD regulated transcripts that escaped prior detection.

Mechanisms of cellular mRNA transcript homeostasis

For most genes, mRNA transcript abundance scales with cell size to ensure a constant concentration. Scaling of mRNA synthesis rates with cell size plays an important role, with regulation of the activity and abundance of RNA polymerase II (Pol II) now emerging as a key point of control. However, there is also considerable evidence for feedback mechanisms that kinetically couple the rates of mRNA synthesis, nuclear export, and degradation to allow cells to compensate for changes in one by adjusting the others. Researchers are beginning to integrate results from these different fields to reveal the mechanisms underlying transcript homeostasis. This will be crucial for moving beyond our current understanding of relative gene expression towards an appreciation of how absolute transcript levels are linked to other aspects of the cellular phenotype.

Post-transcriptional regulation during stress

To remain competitive, cells exposed to stress of varying duration, rapidity of onset, and intensity, have to balance their expenditure on growth and proliferation versus stress protection. To a large degree dependent on the time scale of stress exposure, the different levels of gene expression control: transcriptional, post-transcriptional and post-translational, will be engaged in stress responses. The post-transcriptional level is appropriate for minute-scale responses to transient stress, and for recovery upon return to normal conditions. The turnover rate, translational activity, covalent modifications, and subcellular localisation of RNA species are regulated under stress by multiple cellular pathways. The interplay between these pathways is required to achieve the appropriate signalling intensity and prevent undue triggering of stress-activated pathways at low stress levels, avoid overshoot, and down-regulate the response in a timely fashion. As much of our understanding of post-transcriptional regulation has been gained in yeast, this review is written with a yeast bias, but attempts to generalise to other eukaryotes. It summarises aspects of how post-transcriptional events in eukaryotes mitigate short-term environmental stresses, and how different pathways interact to optimise the stress response under shifting external conditions.

RNA transcription and degradation of Alu retrotransposons depends on sequence features and evolutionary history

Alu elements are one of the most successful groups of RNA retrotransposons and make up 11% of the human genome with over 1 million individual loci. They are linked to genetic defects, increases in sequence diversity, and influence transcriptional activity. Still, their RNA metabolism is poorly understood yet. It is even unclear whether Alu elements are mostly transcribed by RNA Polymerase II or III. We have conducted a transcription shutoff experiment by α-amanitin and metabolic RNA labeling by 4-thiouridine combined with RNA fragmentation (TT-seq) and RNA-seq to shed further light on the origin and life cycle of Alu transcripts. We find that Alu RNAs are more stable than previously thought and seem to originate in part from RNA Polymerase II activity, as previous reports suggest. Their expression however seems to be independent of the transcriptional activity of adjacent genes. Furthermore, we have developed a novel statistical test for detecting the expression of quantitative trait loci in Alu elements that relies on the de Bruijn graph representation of all Alu sequences. It controls for both statistical significance and biological relevance using a tuned k-mer representation, discovering influential sequence features missed by regular motif search. In addition, we discover several point mutations using a generalized linear model, and motifs of interest, which also match transcription factor-binding motifs.

A Novel Dynamical Regulation of mRNA Distribution by Cross-Talking Pathways

In this paper, we use a similar approach to the one proposed by Chen and Jiao to calculate the mathematical formulas of the generating function V(z,t) and the mass function Pm(t) of a cross-talking pathways model in large parameter regions. Together with kinetic rates from yeast and mouse genes, our numerical examples reveal novel bimodal mRNA distributions for intermediate times, whereby the mode of distribution Pm(t) displays unimodality with the peak at m=0 for initial and long times, which has not been obtained in previous works. Such regulation of mRNA distribution exactly matches the transcriptional dynamics for the osmosensitive genes in Saccharomyces cerevisiae, which has not been generated by those models with one single pathway or feedback loops. This paper may provide us with a novel observation on transcriptional distribution dynamics regulated by multiple signaling pathways in response to environmental changes and genetic perturbations.

Quantification of transcription noise’s impact on cell fate commitment with digital resolutions

Motivation

Gene transcription is a random and noisy process. Tremendous efforts in single cell studies have been mapping transcription noises to phenotypic variabilities between isogenic cells. However, the exact role of the noise in cell fate commitment remains largely descriptive or even controversial.

Results

For a specified cell fate, we define the jumping digit I of a critical gene as a statistical threshold that a single cell has approximately an equal chance to commit the fate as to have at least I transcripts of the gene. When the transcription is perturbed by a noise enhancer without changing the basal transcription level E  0, we find a crossing digit k such that the noise catalyzes cell fate change when I &gt; k while stabilizes the current state when I &lt; k; k remains stable against enormous variations of kinetic rates. We further test the reactivation of latent HIV in 22 integration sites by noise enhancers paired with transcriptional activators. Strong synergistic actions are observed when the activators increase transcription burst frequency, whereas no synergism, but antagonism, is often observed if activators increase burst size. The synergistic efficiency can be predicted accurately by the ratio I / E0. When the noise enhancers double the noise, the activators double the burst frequency, and I / E0 ≥ 7, their combination is 10 times more effective than their additive effects across all 22 sites.

Availability and implementation

The jumping digit I may provide a novel probe to explore the phenotypic consequences of transcription noise in cell functions. Code is freely available at http://cam.gzhu.edu.cn/info/1014/1223.htm.

Supplementary information

Supplementary data are available at Bioinformatics online.

Direct analysis of ribosome targeting illuminates thousand-fold regulation of translation initiation

Translational control shapes the proteome in normal and pathophysiological conditions. Current high-throughput approaches reveal large differences in mRNA-specific translation activity but cannot identify the causative mRNA features. We developed direct analysis of ribosome targeting (DART) and used it to dissect regulatory elements within 5' untranslated regions that confer 1,000-fold differences in ribosome recruitment in biochemically accessible cell lysates. Using DART, we determined a functional role for most alternative 5' UTR isoforms expressed in yeast, revealed a general mode of increased translation via direct binding to a core translation factor, and identified numerous translational control elements including C-rich silencers that are sufficient to repress translation both in vitro and in vivo. DART enables systematic assessment of the translational regulatory potential of 5' UTR variants, whether native or disease-associated, and will facilitate engineering of mRNAs for optimized protein production in various systems.

A compensatory link between cleavage/polyadenylation and mRNA turnover regulates steady-state mRNA levels in yeast

Cells have compensatory mechanisms to coordinate the rates of major biological processes, thereby permitting growth in a wide variety of conditions. Here, we uncover a compensatory link between cleavage/polyadenylation in the nucleus and messenger RNA (mRNA) turnover in the cytoplasm. On a global basis, same-gene 3' mRNA isoforms with twofold or greater differences in half-lives have steady-state mRNA levels that differ by significantly less than a factor of 2. In addition, increased efficiency of cleavage/polyadenylation at a specific site is associated with reduced stability of the corresponding 3' mRNA isoform. This inverse relationship between cleavage/polyadenylation and mRNA isoform half-life reduces the variability in the steady-state levels of mRNA isoforms, and it occurs in all four growth conditions tested. These observations suggest that during cleavage/polyadenylation in the nucleus, mRNA isoforms are marked in a manner that persists upon translocation to the cytoplasm and affects the activity of mRNA degradation machinery, thus influencing mRNA stability.