Search

Signaling pathways drive cell fate transitions largely by changing gene expression. However, the mechanisms for rapid and selective transcriptome rewiring in response to signaling cues remain elusive. Here we use deep learning to deconvolve both the sequence determinants and the trans-acting regulators that trigger extracellular signal-regulated kinase (ERK)-mitogen-activated protein kinase kinase (MEK)-induced decay of the naive pluripotency mRNAs. Timing of decay is coupled to embryo implantation through ERK-MEK phosphorylation of LIN28A, which repositions pLIN28A to the highly A+U-rich 3' untranslated region (3'UTR) termini of naive pluripotency mRNAs. Interestingly, these A+U-rich 3'UTR termini serve as poly(A)-binding protein (PABP)-binding hubs, poised for signal-induced convergence with LIN28A. The multivalency of AUU motifs determines the efficacy of pLIN28A-PABP convergence, which enhances PABP 3'UTR binding, decreases the protection of poly(A) tails and activates mRNA decay to enable progression toward primed pluripotency. Thus, the signal-induced convergence of LIN28A with PABP-RNA hubs drives the rapid selection of naive mRNAs for decay, enabling the transcriptome remodeling that ensures swift developmental progression., (© 2024. The Author(s).)

Oncogenic RAS signaling reprograms gene expression through both transcriptional and post-transcriptional mechanisms. While transcriptional regulation downstream of RAS is relatively well characterized, how RAS post-transcriptionally modulates gene expression to promote malignancy remains largely unclear. Using quantitative RNA interactome capture analysis, we here reveal that oncogenic RAS signaling reshapes the RNA-bound proteomic landscape of pancreatic cancer cells, with a network of nuclear proteins centered around nucleolin displaying enhanced RNA-binding activity. We show that nucleolin is phosphorylated downstream of RAS, which increases its binding to pre-ribosomal RNA (rRNA), boosts rRNA production, and promotes ribosome biogenesis. This nucleolin-dependent enhancement of ribosome biogenesis is crucial for RAS-induced pancreatic cancer cell proliferation and can be targeted therapeutically to inhibit tumor growth. Our results reveal that oncogenic RAS signaling drives ribosome biogenesis by regulating the RNA-binding activity of nucleolin and highlight a crucial role for this mechanism in RAS-mediated tumorigenesis., (© 2023 The Authors. Published under the terms of the CC BY 4.0 license.)

The PKCε-regulated genome protective pathway provides transformed cells a failsafe to successfully complete mitosis. Despite the necessary role for Aurora B in this programme, it is unclear whether its requirement is sufficient or if other PKCε cell cycle targets are involved. To address this, we developed a trapping strategy using UV-photocrosslinkable amino acids encoded in the PKCε kinase domain. The validation of the mRNA binding protein SERBP1 as a PKCε substrate revealed a series of mitotic events controlled by the catalytic form of PKCε. PKCε represses protein translation, altering SERBP1 binding to the 40 S ribosomal subunit and promoting the assembly of ribonucleoprotein granules containing SERBP1, termed M-bodies. Independent of Aurora B, SERBP1 is shown to be necessary for chromosome segregation and successful cell division, correlating with M-body formation. This requirement for SERBP1 demonstrates that Aurora B acts in concert with translational regulation in the PKCε-controlled pathway exerting genome protection., (© 2021. The Author(s).)

Mendelian randomisation (MR) analysis is an important tool to elucidate the causal relevance of environmental and biological risk factors for disease. However, causal inference is undermined if genetic variants used to instrument a risk factor also influence alternative disease-pathways (horizontal pleiotropy). Here we report how the 'no horizontal pleiotropy assumption' is strengthened when proteins are the risk factors of interest. Proteins are typically the proximal effectors of biological processes encoded in the genome. Moreover, proteins are the targets of most medicines, so MR studies of drug targets are becoming a fundamental tool in drug development. To enable such studies, we introduce a mathematical framework that contrasts MR analysis of proteins with that of risk factors located more distally in the causal chain from gene to disease. We illustrate key model decisions and introduce an analytical framework for maximising power and evaluating the robustness of analyses.

Background: We characterised the phenotypic consequence of genetic variation at the PCSK9 locus and compared findings with recent trials of pharmacological inhibitors of PCSK9., Methods: Published and individual participant level data (300,000+ participants) were combined to construct a weighted PCSK9 gene-centric score (GS). Seventeen randomized placebo controlled PCSK9 inhibitor trials were included, providing data on 79,578 participants. Results were scaled to a one mmol/L lower LDL-C concentration., Results: The PCSK9 GS (comprising 4 SNPs) associations with plasma lipid and apolipoprotein levels were consistent in direction with treatment effects. The GS odds ratio (OR) for myocardial infarction (MI) was 0.53 (95% CI 0.42; 0.68), compared to a PCSK9 inhibitor effect of 0.90 (95% CI 0.86; 0.93). For ischemic stroke ORs were 0.84 (95% CI 0.57; 1.22) for the GS, compared to 0.85 (95% CI 0.78; 0.93) in the drug trials. ORs with type 2 diabetes mellitus (T2DM) were 1.29 (95% CI 1.11; 1.50) for the GS, as compared to 1.00 (95% CI 0.96; 1.04) for incident T2DM in PCSK9 inhibitor trials. No genetic associations were observed for cancer, heart failure, atrial fibrillation, chronic obstructive pulmonary disease, or Alzheimer's disease - outcomes for which large-scale trial data were unavailable., Conclusions: Genetic variation at the PCSK9 locus recapitulates the effects of therapeutic inhibition of PCSK9 on major blood lipid fractions and MI. While indicating an increased risk of T2DM, no other possible safety concerns were shown; although precision was moderate.

Studies of spliceosomal interactions are challenging due to their dynamic nature. Here we used spliceosome iCLIP, which immunoprecipitates SmB along with small nuclear ribonucleoprotein particles and auxiliary RNA binding proteins, to map spliceosome engagement with pre-messenger RNAs in human cell lines. This revealed seven peaks of spliceosomal crosslinking around branchpoints (BPs) and splice sites. We identified RNA binding proteins that crosslink to each peak, including known and candidate splicing factors. Moreover, we detected the use of over 40,000 BPs with strong sequence consensus and structural accessibility, which align well to nearby crosslinking peaks. We show how the position and strength of BPs affect the crosslinking patterns of spliceosomal factors, which bind more efficiently upstream of strong or proximally located BPs and downstream of weak or distally located BPs. These insights exemplify spliceosome iCLIP as a broadly applicable method for transcriptomic studies of splicing mechanisms.

Recursive splicing (RS) starts by defining an "RS-exon," which is then spliced to the preceding exon, thus creating a recursive 5' splice site (RS-5ss). Previous studies focused on cryptic RS-exons, and now we find that the exon junction complex (EJC) represses RS of hundreds of annotated, mainly constitutive RS-exons. The core EJC factors, and the peripheral factors PNN and RNPS1, maintain RS-exon inclusion by repressing spliceosomal assembly on RS-5ss. The EJC also blocks 5ss located near exon-exon junctions, thus repressing inclusion of cryptic microexons. The prevalence of annotated RS-exons is high in deuterostomes, while the cryptic RS-exons are more prevalent in Drosophila, where EJC appears less capable of repressing RS. Notably, incomplete repression of RS also contributes to physiological alternative splicing of several human RS-exons. Finally, haploinsufficiency of the EJC factor Magoh in mice is associated with skipping of RS-exons in the brain, with relevance to the microcephaly phenotype and human diseases., (Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.)