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The vertebrate ‘neural plate border’ is a transient territory located at the edge of the neural plate containing precursors for all ectodermal derivatives: the neural plate, neural crest, placodes and epidermis. Elegant functional experiments in a range of vertebrate models have provided an in-depth understanding of gene regulatory interactions within the ectoderm. However, these experiments conducted at tissue level raise seemingly contradictory models for fate allocation of individual cells. Here, we carry out single cell RNA sequencing of chick ectoderm from primitive streak to neurulation stage, to explore cell state diversity and heterogeneity. We characterise the dynamics of gene modules, allowing us to model the order of molecular events which take place as ectodermal fates segregate. Furthermore, we find that genes previously classified as neural plate border ‘specifiers’ typically exhibit dynamic expression patterns and are enriched in either neural, neural crest or placodal fates, revealing that the neural plate border should be seen as a heterogeneous ectodermal territory and not a discrete transitional transcriptional state. Analysis of neural, neural crest and placodal markers reveals that individual NPB cells co-express competing transcriptional programmes suggesting that their ultimate identify is not yet fixed. This population of ‘border located undecided progenitors’ (BLUPs) gradually diminishes as cell fate decisions take place. Considering our findings, we propose a probabilistic model for cell fate choice at the neural plate border. Our data suggest that the probability of a progenitor’s daughters to contribute to a given ectodermal derivative is related to the balance of competing transcriptional programmes, which in turn are regulated by the spatiotemporal position of a progenitor.

During early vertebrate development, signals from a special region of the embryo, the organizer, can redirect the fate of non-neural ectoderm cells to form a complete, patterned nervous system. This is called neural induction and has generally been imagined as a single signalling event, causing a switch of fate. Here, we undertake a comprehensive analysis, in very fine time course, of the events following exposure of competent ectoderm of the chick to the organizer (the tip of the primitive streak, Hensen’s node). Using transcriptomics and epigenomics we generate a gene regulatory network comprising 175 transcriptional regulators and 5614 predicted interactions between them, with fine temporal dynamics from initial exposure to the signals to expression of mature neural plate markers. Using in situ hybridization, single-cell RNA-sequencing, and reporter assays, we show that the gene regulatory hierarchy of responses to a grafted organizer closely resembles the events of normal neural plate development. The study is accompanied by an extensive resource, including information about conservation of the predicted enhancers in other vertebrates.

N6- methyladenosine (m6A) RNA modification impacts mRNA fate primarily via reader proteins, which dictate processes in development, stress, and disease. Yet little is known about m6A function in Saccharomyces cerevisiae, which occurs solely during early meiosis. Here, we perform a multifaceted analysis of the m6A reader protein Pho92/Mrb1. Cross-linking immunoprecipitation analysis reveals that Pho92 associates with the 3’end of meiotic mRNAs in both an m6A-dependent and independent manner. Within cells, Pho92 transitions from the nucleus to the cytoplasm, and associates with translating ribosomes. In the nucleus Pho92 associates with target loci through its interaction with transcriptional elongator Paf1C. Functionally, we show that Pho92 promotes and links protein synthesis to mRNA decay. As such, the Pho92-mediated m6A-mRNA decay is contingent on active translation and the CCR4-NOT complex. We propose that the m6A reader Pho92 is loaded co-transcriptionally to facilitate protein synthesis and subsequent decay of m6A modified transcripts, and thereby promotes meiosis.

Prognostic modelling is important in clinical practice and epidemiology for patient management and research. Electronic health records (EHR) provide large quantities of data for such models, but conventional epidemiological approaches require significant researcher time to implement. Expert selection of variables, fine-tuning of variable transformations and interactions, and imputing missing values are time-consuming and could bias subsequent analysis, particularly given that missingness in EHR is both high, and may carry meaning. Using a cohort of 80,000 patients from the CALIBER programme, we compared traditional modelling and machine-learning approaches in EHR. First, we used Cox models and random survival forests with and without imputation on 27 expert-selected, preprocessed variables to predict all-cause mortality. We then used Cox models, random forests and elastic net regression on an extended dataset with 586 variables to build prognostic models and identify novel prognostic factors without prior expert input. We observed that data-driven models used on an extended dataset can outperform conventional models for prognosis, without data preprocessing or imputing missing values. An elastic net Cox regression based with 586 unimputed variables with continuous values discretised achieved a C-index of 0.801 (bootstrapped 95% CI 0.799 to 0.802), compared to 0.793 (0.791 to 0.794) for a traditional Cox model comprising 27 expert-selected variables with imputation for missing values. We also found that data-driven models allow identification of novel prognostic variables; that the absence of values for particular variables carries meaning, and can have significant implications for prognosis; and that variables often have a nonlinear association with mortality, which discretised Cox models and random forests can elucidate. This demonstrates that machine-learning approaches applied to raw EHR data can be used to build models for use in research and clinical practice, and identify novel predictive variables and their effects to inform future research.

Hi-C is one of the main methods for investigating spatial co-localisation of DNA in the nucleus. However, the raw sequencing data obtained from Hi-C experiments suffer from large biases and spurious contacts, making it difficult to identify true interactions. Existing methods use complex models to account for biases and do not provide a significance threshold for detecting interactions. Here we introduce a simple binomial probabilistic model that resolves complex biases and distinguishes between true and false interactions. The model corrects biases of known and unknown origin and yields a p-value for each interaction, providing a reliable threshold based on significance. We demonstrate this experimentally by testing the method against a random ligation dataset. Our method outperforms previous methods and provides a statistical framework for further data analysis, such as comparisons of Hi-C interactions between different conditions. GOTHiC is available as a BioConductor package (http://www.bioconductor.org/packages/release/bioc/html/GOTHiC.html).

Glioblastoma multiforme (GBM) is the most aggressive human primary brain cancer. Using a Trp53-deficient mouse model of GBM, we show that genetic inactivation of the Atm cofactor Atmin, which is dispensable for embryonic and adult neural development, strongly suppresses GBM formation. Mechanistically, expression of several GBM-associated genes, including Pdgfra, was normalized by Atmin deletion in the Trp53-null background. Pharmacological ATM inhibition also reduced Pdgfra expression, and reduced the proliferation of Trp53-deficient primary glioma cells from murine and human tumors, while normal neural stem cells were unaffected. Analysis of GBM datasets showed that PDGFRA expression is also significantly increased in human TP53-mutant compared with TP53-wild-type tumors. Moreover, combined treatment with ATM and PDGFRA inhibitors efficiently killed TP53-mutant primary human GBM cells, but not untransformed neural stem cells. These results reveal a new requirement for ATMIN-dependent ATM signaling in TP53-deficient GBM, indicating a pro-tumorigenic role for ATM in the context of these tumors.

Transcriptional control ensures genes are expressed in the right amounts at the correct times and locations. Understanding quantitatively how regulatory systems convert input signals to appropriate outputs remains a challenge. For the first time, we successfully model even skipped (eve) stripes 2 and 3+7 across the entire fly embryo at cellular resolution. A straightforward statistical relationship explains how transcription factor (TF) concentrations define eve’s complex spatial expression, without the need for pairwise interactions or cross-regulatory dynamics. Simulating thousands of TF combinations, we recover known regulators and suggest new candidates. Finally, we accurately predict the intricate effects of perturbations including TF mutations and misexpression. Our approach imposes minimal assumptions about regulatory function; instead we infer underlying mechanisms from models that best fit the data, like the lack of TF-specific thresholds and the positional value of homotypic interactions. Our study provides a general and quantitative method for elucidating the regulation of diverse biological systems.

MOF is the major histone H4 lysine 16-specific (H4K16) acetyltransferase in mammals and Drosophila. In flies, it is involved in the regulation of X-chromosomal and autosomal genes as part of the MSL and the NSL complexes, respectively. While the function of the MSL complex as a dosage compensation regulator is fairly well understood, the role of the NSL complex in gene regulation is still poorly characterized. Here we report a comprehensive ChIP-seq analysis of four NSL complex members (NSL1, NSL3, MBD-R2, and MCRS2) throughout the Drosophila melanogaster genome. Strikingly, the majority (85.5%) of NSL-bound genes are constitutively expressed across different cell types. We find that an increased abundance of the histone modifications H4K16ac, H3K4me2, H3K4me3, and H3K9ac in gene promoter regions is characteristic of NSL-targeted genes. Furthermore, we show that these genes have a well-defined nucleosome free region and broad transcription initiation patterns. Finally, by performing ChIP-seq analyses of RNA polymerase II (Pol II) in NSL1- and NSL3-depleted cells, we demonstrate that both NSL proteins are required for efficient recruitment of Pol II to NSL target gene promoters. The observed Pol II reduction coincides with compromised binding of TBP and TFIIB to target promoters, indicating that the NSL complex is required for optimal recruitment of the pre-initiation complex on target genes. Moreover, genes that undergo the most dramatic loss of Pol II upon NSL knockdowns tend to be enriched in DNA Replication-related Element (DRE). Taken together, our findings show that the MOF-containing NSL complex acts as a major regulator of housekeeping genes in flies by modulating initiation of Pol II transcription.

The regulation of alternative splicing involves interactions between RNA-binding proteins and pre-mRNA positions close to the splice sites. T-cell intracellular antigen 1 (TIA1) and TIA1-like 1 (TIAL1) locally enhance exon inclusion by recruiting U1 snRNP to 5' splice sites. However, effects of TIA proteins on splicing of distal exons have not yet been explored. We used UV-crosslinking and immunoprecipitation (iCLIP) to find that TIA1 and TIAL1 bind at the same positions on human RNAs. Binding downstream of 5' splice sites was used to predict the effects of TIA proteins in enhancing inclusion of proximal exons and silencing inclusion of distal exons. The predictions were validated in an unbiased manner using splice-junction microarrays, RT-PCR, and minigene constructs, which showed that TIA proteins maintain splicing fidelity and regulate alternative splicing by binding exclusively downstream of 5' splice sites. Surprisingly, TIA binding at 5' splice sites silenced distal cassette and variable-length exons without binding in proximity to the regulated alternative 3' splice sites. Using transcriptome-wide high-resolution mapping of TIA-RNA interactions we evaluated the distal splicing effects of TIA proteins. These data are consistent with a model where TIA proteins shorten the time available for definition of an alternative exon by enhancing recognition of the preceding 5' splice site. Thus, our findings indicate that changes in splicing kinetics could mediate the distal regulation of alternative splicing.

Transcriptional regulation is one of the most important processes for modulating gene expression. Though much of this control is attributed to transcription factors, histones, and associated enzymes, it is increasingly apparent that the spatial organization of chromosomes within the nucleus has a profound effect on transcriptional activity. Studies in yeast indicate that the nuclear pore complex might promote transcription by recruiting chromatin to the nuclear periphery. In higher eukaryotes, however, it is not known whether such regulation has global significance. Here we establish nucleoporins as a major class of global regulators for gene expression in Drosophila melanogaster. Using chromatin-immunoprecipitation combined with microarray hybridisation, we show that Nup153 and Megator (Mtor) bind to 25% of the genome in continuous domains extending 10 kb to 500 kb. These Nucleoporin-Associated Regions (NARs) are dominated by markers for active transcription, including high RNA polymerase II occupancy and histone H4K16 acetylation. RNAi-mediated knock-down of Nup153 alters the expression of approximately 5,700 genes, with a pronounced down-regulatory effect within NARs. We find that nucleoporins play a central role in coordinating dosage compensation-an organism-wide process involving the doubling of expression of the male X chromosome. NARs are enriched on the male X chromosome and occupy 75% of this chromosome. Furthermore, Nup153-depletion abolishes the normal function of the male-specific dosage compensation complex. Finally, by extensive 3D imaging, we demonstrate that NARs contribute to gene expression control irrespective of their sub-nuclear localization. Therefore, we suggest that NAR-binding is used for chromosomal organization that enables gene expression control.