Although it is generally accepted that cellular differentiation requires changes to transcriptional networks, dynamic regulation of promoters and enhancers at specific sets of genes has not been previously studied en masse. Exploiting the fact that active promoters and enhancers are transcribed, we simultaneously measured their activity in 19 human and 14 mouse time courses covering a wide range of cell types and biological stimuli. Enhancer RNAs, then messenger RNAs encoding transcription factors, dominated the earliest responses. Binding sites for key lineage transcription factors were simultaneously overrepresented in enhancers and promoters active in each cellular system. Our data support a highly generalizable model in which enhancer transcription is the earliest event in successive waves of transcriptional change during cellular differentiation or activation.

MicroRNAs (miRNAs) are short non-coding RNAs with key roles in cellular regulation. As part of the fifth edition of the Functional Annotation of Mammalian Genome (FANTOM5) project, we created an integrated expression atlas of miRNAs and their promoters by deep-sequencing 492 short RNA (sRNA) libraries, with matching Cap Analysis Gene Expression (CAGE) data, from 396 human and 47 mouse RNA samples. Promoters were identified for 1,357 human and 804 mouse miRNAs and showed strong sequence conservation between species. We also found that primary and mature miRNA expression levels were correlated, allowing us to use the primary miRNA measurements as a proxy for mature miRNA levels in a total of 1,829 human and 1,029 mouse CAGE libraries. We thus provide a broad atlas of miRNA expression and promoters in primary mammalian cells, establishing a foundation for detailed analysis of miRNA expression patterns and transcriptional control regions.

The RNA exosome is fundamental for the degradation of RNA in eukaryotic nuclei. Substrate targeting is facilitated by its co-factor Mtr4p/hMTR4, which links to RNA-binding protein adaptors. One example is the trimeric human nuclear exosome targeting (NEXT) complex, which is composed of hMTR4, the Zn-finger protein ZCCHC8, and the RNA-binding factor RBM7. NEXT primarily targets early and unprocessed transcripts, which demands a rationale for how the nuclear exosome recognizes processed RNAs. Here, we describe the poly(A) tail exosome targeting (PAXT) connection, which comprises the ZFC3H1 Zn-knuckle protein as a central link between hMTR4 and the nuclear poly(A)-binding protein PABPN1. Individual depletion of ZFC3H1 and PABPN1 results in the accumulation of common transcripts that are generally both longer and more extensively polyadenylated than NEXT substrates. Importantly, ZFC3H1/PABPN1 and ZCCHC8/RBM7 contact hMTR4 in a mutually exclusive manner, revealing that the exosome targets nuclear transcripts of different maturation status by substituting its hMTR4-associating adaptors.

Glioblastoma (World Health Organization grade IV glioma) represents the most common primary, intrinsic brain tumor with inevitable recurrence, limiting the median survival of patients to little more than a year ( 1, 2 ). Glioblastomas display cellular hierarchies with self-renewing glioblastoma stem cells (GSC) at the apex, with contributions of GSCs to therapeutic resistance and tumor recurrence ( 3-5 ). Standard-of-care therapy includes surgical resection followed by combined radiotherapy and chemotherapy, and then adjuvant chemotherapy, but treatment remains palliative ( 6 ). Given the roles of GSCs in therapeutic resistance, angiogenesis, immune escape, and invasion, clinical and preclinical observations suggest that targeting GSCs may improve tumor outcome ( 7 ). SIGNIFICANCE:Epitranscriptomics promotes cellular heterogeneity in cancer. RNA m6A landscapes of cancer and NSCs identifi ed cell type-specifi c dependencies and therapeutic vulnerabilities. The m6A reader YTHDF2 stabilized MYC mRNA specifi cally in cancer stem cells. Given the challenge of targeting MYC, YTHDF2 presents a therapeutic target to perturb MYC signaling in glioblastoma.Research.

Alternative usage of transcript isoforms from the same gene has been hypothesized as an important feature in cancers. However, differential usage of gene transcripts between conditions (isoform switching) has not been comprehensively characterized in and across cancer types. To this end, we developed methods for identification and visualization of isoform switches with predicted functional consequences. Using these methods, we characterized isoform switching in RNA-seq data from >5,500 cancer patients covering 12 solid cancer types. Isoform switches with potential functional consequences were common, affecting approximately 19% of multiple transcript genes. Among these, isoform switches leading to loss of DNA sequence encoding protein domains were more frequent than expected, particularly in pancancer switches. We identified several isoform switches as powerful biomarkers: 31 switches were highly predictive of patient survival independent of cancer types. Our data constitute an important resource for cancer researchers, available through interactive web tools. Moreover, our methods, available as an R package, enable systematic analysis of isoform switches from other RNA-seq datasets. This study indicates that isoform switches with predicted functional consequences are common and important in dysfunctional cells, which in turn means that gene expression should be analyzed at the isoform level. http://mcr.aacrjournals.org/content/molcanres/15/9/1206/F1.large.jpg..