Structural basis of Nrd1–Nab3 heterodimerization

Heterodimerization of RNA binding proteins Nrd1 and Nab3 is essential to communicate the RNA recognition in the nascent transcript with the Nrd1 recognition of the Ser5-phosphorylated Rbp1 C-terminal domain in RNA polymerase II. The structure of a Nrd1–Nab3 chimera reveals the basis of heterodimerization, filling a missing gap in knowledge of this system. The free form of the Nrd1 interaction domain of Nab3 (NRID) forms a multi-state three-helix bundle that is clamped in a single conformation upon complex formation with the Nab3 interaction domain of Nrd1 (NAID). The latter domain forms two long helices that wrap around NRID, resulting in an extensive protein–protein interface that would explain the highly favorable free energy of heterodimerization. Mutagenesis of some conserved hydrophobic residues involved in the heterodimerization leads to temperature-sensitive phenotypes, revealing the importance of this interaction in yeast cell fitness. The Nrd1–Nab3 structure resembles the previously reported Rna14/Rna15 heterodimer structure, which is part of the poly(A)-dependent termination pathway, suggesting that both machineries use similar structural solutions despite they share little sequence homology and are potentially evolutionary divergent.

Structural Probing with MNase Tethered to Ribosome Assembly Factors Resolves Flexible RNA Regions within the Nascent Pre-Ribosomal RNA

The synthesis of ribosomes involves the correct folding of the pre-ribosomal RNA within pre-ribosomal particles. The first ribosomal precursor or small subunit processome assembles stepwise on the nascent transcript of the 35S gene. At the earlier stages, the pre-ribosomal particles undergo structural and compositional changes, resulting in heterogeneous populations of particles with highly flexible regions. Structural probing methods are suitable for resolving these structures and providing evidence about the architecture of ribonucleoprotein complexes. Our approach used MNase tethered to the assembly factors Nan1/Utp17, Utp10, Utp12, and Utp13, which among other factors, initiate the formation of the small subunit processome. Our results provide dynamic information about the folding of the pre-ribosomes by elucidating the relative organization of the 5′ETS and ITS1 regions within the 35S and U3 snoRNA around the C-terminal domains of Nan1/Utp17, Utp10, Utp12, and Utp13.

Accurate inference of stochastic gene expression from nascent transcript heterogeneity

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. It is thus unclear how accurately the inferred parameters reflect transcription. To address these issues, 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 stage. We infer transcriptional parameters from mature and nascent mRNA distributions, with and without accounting for cell cycle stage and compare the results to live-cell transcription measurements of the same gene. We conclude that: (i) not accounting for cell cycle dynamics in nascent mRNA data overestimates the magnitude of promoter switching rates and the initiation rate, and underestimates the fraction of time spent in the active state and the burst size. (ii) use of mature mRNA data, instead of nascent data, significantly increases the errors in parameter estimation and can mistakenly classify a gene as non-bursting. Furthermore, we show how to correctly adjust for measurement noise in smFISH at low nascent transcript numbers. Simulations with parameters estimated from nascent smFISH data corrected for cell cycle phases and measurement noise leads to autocorrelation functions that agree with those obtained from live-cell imaging. Therefore, our novel data curation method yields a quantitatively accurate picture of gene expression.

A thermodynamic model of bacterial transcription

Transcriptional pausing is highly regulated by the template DNA and nascent transcript sequences. Here, we propose a thermodynamic model of transcriptional pausing, based on the thermal energy of transcription bubbles and nascent RNA structures, to describe the kinetics of the reaction pathways between active translocation, intermediate, backtracked, and hairpin-stabilized pauses. The model readily predicts experimentally detected pauses in high-resolution optical tweezers measurements of transcription. Unlike other models, it also predicts the effect of tension and the GreA transcription factor on pausing.

Transcription and splicing dynamics during early Drosophila development

Widespread co-transcriptional splicing has been demonstrated from yeast to human. However, most studies to date addressing the kinetics of splicing relative to transcription used either Saccharomyces cerevisiae or metazoan cultured cell lines. Here, we adapted native elongating transcript sequencing technology (NET-seq) to measure co-transcriptional splicing dynamics during the early developmental stages of Drosophila melanogaster embryos. Our results reveal the position of RNA polymerase II (Pol II) when both canonical and recursive splicing occur. We found heterogeneity in splicing dynamics, with some RNAs spliced immediately after intron transcription, whereas for other transcripts no splicing was observed over the first 100 nucleotides of the downstream exon. Introns that show splicing completion before Pol II has reached the end of the downstream exon are necessarily intron-defined. We studied the splicing dynamics of both nascent pre-mRNAs transcribed in the early embryo, which have few and short introns, as well as pre-mRNAs transcribed later in embryonic development, which contain multiple long introns. As expected, we found a relationship between the proportion of spliced reads and intron size. However, intron definition was observed at all intron sizes. We further observed that genes transcribed in the early embryo tend to be isolated in the genome whereas genes transcribed later are often overlapped by a neighboring convergent gene. In isolated genes, transcription termination occurred soon after the polyadenylation site, while in overlapped genes Pol II persisted associated with the DNA template after cleavage and polyadenylation of the nascent transcript. Taken together, our data unravels novel dynamic features of Pol II transcription and splicing in the developing Drosophila embryo.

R-Loops between nascent pri-miRNAs and the encoding loci promote co-transcriptional processing of miRNAs in plants

SummaryIn most organisms, the maturation of nascent RNAs is coupled to transcription, undergoing many processing steps co-transcriptionally. Unlike in animals, the RNA polymerase II (RNAPII) transcribes microRNAs (miRNAs) as long and structurally variable pri-miRNAs in plants. Current evidence suggests that the miRNA biogenesis complex assembly initiates early during the transcription of pri-miRNAs in plants. However, it is unknown whether miRNA processing occurs co-transcriptionally. Here, we show that plant miRNA biogenesis is coupled to transcription in a process that relies on the formation of DNA:RNA hybrids (R-loops) between the nascent transcript and the encoding loci. We used native elongating transcript sequencing data and imaging techniques to demonstrate that plant miRNA biogenesis occurs co-transcriptionally. We found that the entire biogenesis occurs coupled to transcription for pri-miRNAs processed from the loop but requires a second nucleoplasmic step for those processed from the base of the hairpin. Furthermore, we found that co- and post-transcriptional miRNA processing mechanisms co-exist for most miRNAs in a dynamic balance. Notably, we discovered that R-loops between the 5’-end single-stranded arm of the pri-miRNAs and the encoding loci anchor the transcript, promoting co-transcriptional processing. Our data demonstrate the coupling of transcription and miRNA processing in plants and discovered an unexpected function for R-loops promoting RNA processing. Furthermore, our results suggest the neo-functionalization of co-transcriptionally processed miRNAs, boosting countless regulatory scenarios.

Myotubularin-related phosphatase 5 is a critical determinant of autophagy in neurons

Autophagy is a conserved, multi-step process of capturing proteolytic cargo in autophagosomes for lysosome degradation. The capacity to remove toxic proteins that accumulate in neurodegenerative disorders attests to the disease-modifying potential of the autophagy pathway. However, neurons respond only marginally to conventional methods for inducing autophagy, limiting efforts to develop therapeutic autophagy modulators for neurodegenerative diseases. The determinants underlying poor autophagy induction in neurons and the degree to which neurons and other cell types are differentially sensitive to autophagy stimuli are incompletely defined. Accordingly, we sampled nascent transcript synthesis and stabilities in fibroblasts, induced pluripotent stem cells (iPSCs) and iPSC-derived neurons (iNeurons), thereby uncovering a neuron-specific stability of transcripts encoding myotubularin-related phosphatase 5 (MTMR5). MTMR5 is an autophagy suppressor that acts with its binding partner, MTMR2, to dephosphorylate phosphoinositides critical for autophagy initiation and autophagosome maturation. We found that MTMR5 is necessary and sufficient to suppress autophagy in iNeurons and undifferentiated iPSCs. Using optical pulse labeling to visualize the turnover of endogenously-encoded proteins in live cells, we observed that knockdown of MTMR5 or MTMR2, but not MTMR9, significantly enhances neuronal degradation of TDP-43, an autophagy substrate implicated in several neurodegenerative diseases. Accordingly, our findings establish a regulatory mechanism of autophagy intrinsic to neurons and targetable for clearing disease-related proteins in a cell type-specific manner. In so doing, our results not only unravel novel aspects of neuronal biology and proteostasis, but also elucidate a strategy for modulating neuronal autophagy that could be of high therapeutic potential for multiple neurodegenerative diseases.

Enhancer-promoter interactions and transcription are maintained upon acute loss of CTCF, cohesin, WAPL, and YY1

It remains unclear why acute depletion of CTCF and cohesin only marginally affects expression of most genes despite substantially perturbing 3D genome folding at the level of domains and structural loops. To address this conundrum, we used high-resolution Micro-C and nascent transcript profiling to find that enhancer-promoter (E-P) interactions are largely insensitive to acute (3-hour) depletion of CTCF, cohesin, and WAPL. YY1 has been proposed to be a structural regulator of E-P loops, but acute YY1 depletion also had minimal effects on E-P loops, transcription, and 3D genome folding. Strikingly, live-cell single-molecule imaging revealed that cohesin depletion reduced transcription factor binding to chromatin. Thus, although neither CTCF, cohesin, WAPL, nor YY1 are required for the short-term maintenance of most E-P interactions and gene expression, we propose that cohesin may serve as a "transcription factor binding platform" that facilitates transcription factor binding to chromatin.