Transcriptome-wide sites of collided ribosomes reveal principles of translational pausing.

Translation initiation is the major regulatory step defining the rate of protein production from an mRNA. Meanwhile, the impact of nonuniform ribosomal elongation rates is largely unknown. Using a modified ribosome profiling protocol based on footprints from two closely packed ribosomes (disomes), we have mapped ribosomal collisions transcriptome-wide in mouse liver. We uncover that the stacking of an elongating onto a paused ribosome occurs frequently and scales with translation rate, trapping ∼10% of translating ribosomes in the disome state. A distinct class of pause sites is indicative of deterministic pausing signals. Pause site association with specific amino acids, peptide motifs, and nascent polypeptide structure is suggestive of programmed pausing as a widespread mechanism associated with protein folding. Evolutionary conservation at disome sites indicates functional relevance of translational pausing. Collectively, our disome profiling approach allows unique insights into gene regulation occurring at the step of translation elongation.

Mammalian RNA Decay Pathways Are Highly Specialized and Widely Linked to Translation.

RNA decay is crucial for mRNA turnover and surveillance and misregulated in many diseases. This complex system is challenging to study, particularly in mammals, where it remains unclear whether decay pathways perform specialized versus redundant roles. Cytoplasmic pathways and links to translation are particularly enigmatic. By directly profiling decay factor targets and normal versus aberrant translation in mouse embryonic stem cells (mESCs), we uncovered extensive decay pathway specialization and crosstalk with translation. XRN1 (5'-3') mediates cytoplasmic bulk mRNA turnover whereas SKIV2L (3'-5') is universally recruited by ribosomes, tackling aberrant translation and sometimes modulating mRNA abundance. Further exploring translation surveillance revealed AVEN and FOCAD as SKIV2L interactors. AVEN prevents ribosome stalls at structured regions, which otherwise require SKIV2L for clearance. This pathway is crucial for histone translation, upstream open reading frame (uORF) regulation, and counteracting ribosome arrest on small ORFs. In summary, we uncovered key targets, components, and functions of mammalian RNA decay pathways and extensive coupling to translation.

Guidelines for Genome-Scale Analysis of Biological Rhythms.

Genome biology approaches have made enormous contributions to our understanding of biological rhythms, particularly in identifying outputs of the clock, including RNAs, proteins, and metabolites, whose abundance oscillates throughout the day. These methods hold significant promise for future discovery, particularly when combined with computational modeling. However, genome-scale experiments are costly and laborious, yielding "big data" that are conceptually and statistically difficult to analyze. There is no obvious consensus regarding design or analysis. Here we discuss the relevant technical considerations to generate reproducible, statistically sound, and broadly useful genome-scale data. Rather than suggest a set of rigid rules, we aim to codify principles by which investigators, reviewers, and readers of the primary literature can evaluate the suitability of different experimental designs for measuring different aspects of biological rhythms. We introduce CircaInSilico, a web-based application for generating synthetic genome biology data to benchmark statistical methods for studying biological rhythms. Finally, we discuss several unmet analytical needs, including applications to clinical medicine, and suggest productive avenues to address them.

Translational contributions to tissue specificity in rhythmic and constitutive gene expression.

BACKGROUND: The daily gene expression oscillations that underlie mammalian circadian rhythms show striking differences between tissues and involve post-transcriptional regulation. Both aspects remain poorly understood. We have used ribosome profiling to explore the contribution of translation efficiency to temporal gene expression in kidney and contrasted our findings with liver data available from the same mice. RESULTS: Rhythmic translation of constantly abundant messenger RNAs (mRNAs) affects largely non-overlapping transcript sets with distinct phase clustering in the two organs. Moreover, tissue differences in translation efficiency modulate the timing and amount of protein biosynthesis from rhythmic mRNAs, consistent with organ specificity in clock output gene repertoires and rhythmicity parameters. Our comprehensive datasets provided insights into translational control beyond temporal regulation. Between tissues, many transcripts show differences in translation efficiency, which are, however, of markedly smaller scale than mRNA abundance differences. Tissue-specific changes in translation efficiency are associated with specific transcript features and, intriguingly, globally counteracted and compensated transcript abundance variations, leading to higher similarity at the level of protein biosynthesis between both tissues. CONCLUSIONS: We show that tissue specificity in rhythmic gene expression extends to the translatome and contributes to define the identities, the phases and the expression levels of rhythmic protein biosynthesis. Moreover, translational compensation of transcript abundance divergence leads to overall higher similarity at the level of protein production across organs. The unique resources provided through our study will serve to address fundamental questions of post-transcriptional control and differential gene expression in vivo.

Analyzing the temporal regulation of translation efficiency in mouse liver.

Mammalian physiology and behavior follow daily rhythms that are orchestrated by endogenous timekeepers known as circadian clocks. Rhythms in transcription are considered the main mechanism to engender rhythmic gene expression, but important roles for posttranscriptional mechanisms have recently emerged as well (reviewed in Lim and Allada (2013) [1]). We have recently reported on the use of ribosome profiling (RPF-seq), a method based on the high-throughput sequencing of ribosome protected mRNA fragments, to explore the temporal regulation of translation efficiency (Janich et al., 2015 [2]). Through the comparison of around-the-clock RPF-seq and matching RNA-seq data we were able to identify 150 genes, involved in ribosome biogenesis, iron metabolism and other pathways, whose rhythmicity is generated entirely at the level of protein synthesis. The temporal transcriptome and translatome data sets from this study have been deposited in NCBI's Gene Expression Omnibus under the accession number GSE67305. Here we provide additional information on the experimental setup and on important optimization steps pertaining to the ribosome profiling technique in mouse liver and to data analysis.

Ribosome profiling reveals the rhythmic liver translatome and circadian clock regulation by upstream open reading frames.

Mammalian gene expression displays widespread circadian oscillations. Rhythmic transcription underlies the core clock mechanism, but it cannot explain numerous observations made at the level of protein rhythmicity. We have used ribosome profiling in mouse liver to measure the translation of mRNAs into protein around the clock and at high temporal and nucleotide resolution. We discovered, transcriptome-wide, extensive rhythms in ribosome occupancy and identified a core set of approximately 150 mRNAs subject to particularly robust daily changes in translation efficiency. Cycling proteins produced from nonoscillating transcripts revealed thus-far-unknown rhythmic regulation associated with specific pathways (notably in iron metabolism, through the rhythmic translation of transcripts containing iron responsive elements), and indicated feedback to the rhythmic transcriptome through novel rhythmic transcription factors. Moreover, estimates of relative levels of core clock protein biosynthesis that we deduced from the data explained known features of the circadian clock better than did mRNA expression alone. Finally, we identified uORF translation as a novel regulatory mechanism within the clock circuitry. Consistent with the occurrence of translated uORFs in several core clock transcripts, loss-of-function of Denr, a known regulator of reinitiation after uORF usage and of ribosome recycling, led to circadian period shortening in cells. In summary, our data offer a framework for understanding the dynamics of translational regulation, circadian gene expression, and metabolic control in a solid mammalian organ.

A neuron-specific deletion of the microRNA-processing enzyme DICER induces severe but transient obesity in mice.

MicroRNAs (miRNAs) are small, non-coding RNA molecules that regulate gene expression post-transcriptionally. MiRNAs are implicated in various biological processes associated with obesity, including adipocyte differentiation and lipid metabolism. We used a neuronal-specific inhibition of miRNA maturation in adult mice to study the consequences of miRNA loss on obesity development. Camk2a-CreERT2 (Cre+) and floxed Dicer (Dicerlox/lox) mice were crossed to generate tamoxifen-inducible conditional Dicer knockouts (cKO). Vehicle- and/or tamoxifen-injected Cre+;Dicerlox/lox and Cre+;Dicer+/+ served as controls. Four cohorts were used to a) measure body composition, b) follow food intake and body weight dynamics, c) evaluate basal metabolism and effects of food deprivation, and d) assess the brain transcriptome consequences of miRNA loss. cKO mice developed severe obesity and gained 18 g extra weight over the 5 weeks following tamoxifen injection, mainly due to increased fat mass. This phenotype was highly reproducible and observed in all 38 cKO mice recorded and in none of the controls, excluding possible effects of tamoxifen or the non-induced transgene. Development of obesity was concomitant with hyperphagia, increased food efficiency, and decreased activity. Surprisingly, after reaching maximum body weight, obese cKO mice spontaneously started losing weight as rapidly as it was gained. Weight loss was accompanied by lowered O2-consumption and respiratory-exchange ratio. Brain transcriptome analyses in obese mice identified several obesity-related pathways (e.g. leptin, somatostatin, and nemo-like kinase signaling), as well as genes involved in feeding and appetite (e.g. Pmch, Neurotensin) and in metabolism (e.g. Bmp4, Bmp7, Ptger1, Cox7a1). A gene cluster with anti-correlated expression in the cerebral cortex of post-obese compared to obese mice was enriched for synaptic plasticity pathways. While other studies have identified a role for miRNAs in obesity, we here present a unique model that allows for the study of processes involved in reversing obesity. Moreover, our study identified the cortex as a brain area important for body weight homeostasis.

MicroRNAs shape circadian hepatic gene expression on a transcriptome-wide scale.

A considerable proportion of mammalian gene expression undergoes circadian oscillations. Post-transcriptional mechanisms likely make important contributions to mRNA abundance rhythms. We have investigated how microRNAs (miRNAs) contribute to core clock and clock-controlled gene expression using mice in which miRNA biogenesis can be inactivated in the liver. While the hepatic core clock was surprisingly resilient to miRNA loss, whole transcriptome sequencing uncovered widespread effects on clock output gene expression. Cyclic transcription paired with miRNA-mediated regulation was thus identified as a frequent phenomenon that affected up to 30% of the rhythmic transcriptome and served to post-transcriptionally adjust the phases and amplitudes of rhythmic mRNA accumulation. However, only few mRNA rhythms were actually generated by miRNAs. Overall, our study suggests that miRNAs function to adapt clock-driven gene expression to tissue-specific requirements. Finally, we pinpoint several miRNAs predicted to act as modulators of rhythmic transcripts, and identify rhythmic pathways particularly prone to miRNA regulation.DOI: http://dx.doi.org/10.7554/eLife.02510.001.