New insight into the catalytic -dependent and -independent roles of METTL3 in sustaining aberrant translation in chronic myeloid leukemia.

Chronic myeloid leukemia (CML) is a myeloproliferative neoplasm caused by the presence of tyrosine kinase BCR-ABL1 fusion protein, which deregulate transcription and mRNA translation. Tyrosine kinase inhibitors (TKIs) are the first-choice treatment. However, resistance to TKIs remains a challenge to cure CML patients. Here, we reveal that the m6A methyltransferase complex METTL3/METTL14 is upregulated in CML patients and that is required for proliferation of primary CML cells and CML cell lines sensitive and resistant to the TKI imatinib. We demonstrate that depletion of METTL3 strongly impairs global translation efficiency. In particular, our data show that METTL3 is crucial for the expression of genes involved in ribosome biogenesis and translation. Specifically, we found that METTL3 directly regulates the level of PES1 protein identified as an oncogene in several tumors. We propose a model in which nuclear METTL3/METTL14 methyltransferase complex modified nascent transcripts whose translation is enhanced by cytoplasmic localization of METTL3, independently from its catalytic activity. In conclusion, our results point to METTL3 as a novel relevant oncogene in CML and as a promising therapeutic target for TKI resistant CML.

Identification of Genes Post-Transcriptionally Regulated from RNA-seq: The Case Study of Liver Hepatocellular Carcinoma.

The field of transcriptional regulation generally assumes that changes in transcripts levels reflect changes in transcriptional status of the corresponding gene. While this assumption might hold true for a large population of transcripts, a considerable and still unrecognized fraction of the variation might involve other steps of the RNA lifecycle, that is the processing of the premature RNA, and degradation of the mature RNA. Discrimination between these layers requires complementary experimental techniques, such as RNA metabolic labeling or block of transcription experiments. Nonetheless, the analysis of the premature and mature RNA, derived from intronic and exonic read counts in RNA-seq data, allows distinguishing between transcriptionally and post-transcriptionally regulated genes, although not recognizing the specific step involved in the post-transcriptional response, that is processing, degradation, or a combination of the two. We illustrate how the INSPEcT R/Bioconductor package could be used to infer post-transcriptional regulation in TCGA RNA-seq samples for Hepatocellular Carcinoma.

An early Myc-dependent transcriptional program orchestrates cell growth during B-cell activation.

Upon activation, lymphocytes exit quiescence and undergo substantial increases in cell size, accompanied by activation of energy-producing and anabolic pathways, widespread chromatin decompaction, and elevated transcriptional activity. These changes depend upon prior induction of the Myc transcription factor, but how Myc controls them remains unclear. We addressed this issue by profiling the response to LPS stimulation in wild-type and c-myc-deleted primary mouse B-cells. Myc is rapidly induced, becomes detectable on virtually all active promoters and enhancers, but has no direct impact on global transcriptional activity. Instead, Myc contributes to the swift up- and down-regulation of several hundred genes, including many known regulators of the aforementioned cellular processes. Myc-activated promoters are enriched for E-box consensus motifs, bind Myc at the highest levels, and show enhanced RNA Polymerase II recruitment, the opposite being true at down-regulated loci. Remarkably, the Myc-dependent signature identified in activated B-cells is also enriched in Myc-driven B-cell lymphomas: hence, besides modulation of new cancer-specific programs, the oncogenic action of Myc may largely rely on sustained deregulation of its normal physiological targets.

m6A-Dependent RNA Dynamics in T Cell Differentiation.

N6-methyladenosine (m6A) is the most abundant RNA modification. It has been involved in the regulation of RNA metabolism, including degradation and translation, in both physiological and disease conditions. A recent study showed that m6A-mediated degradation of key transcripts also plays a role in the control of T cells homeostasis and IL-7 induced differentiation. We re-analyzed the omics data from that study and, through the integrative analysis of total and nascent RNA-seq data, we were able to comprehensively quantify T cells RNA dynamics and how these are affected by m6A depletion. In addition to the expected impact on RNA degradation, we revealed a broader effect of m6A on RNA dynamics, which included the alteration of RNA synthesis and processing. Altogether, the combined action of m6A on all major steps of the RNA life-cycle closely re-capitulated the observed changes in the abundance of premature and mature RNA species. Ultimately, our re-analysis extended the findings of the initial study, focused on RNA stability, and proposed a yet unappreciated role for m6A in RNA synthesis and processing dynamics.

Integrative analysis of RNA polymerase II and transcriptional dynamics upon MYC activation.

Overexpression of the MYC transcription factor causes its widespread interaction with regulatory elements in the genome but leads to the up- and down-regulation of discrete sets of genes. The molecular determinants of these selective transcriptional responses remain elusive. Here, we present an integrated time-course analysis of transcription and mRNA dynamics following MYC activation in proliferating mouse fibroblasts, based on chromatin immunoprecipitation, metabolic labeling of newly synthesized RNA, extensive sequencing, and mathematical modeling. Transcriptional activation correlated with the highest increases in MYC binding at promoters. Repression followed a reciprocal scenario, with the lowest gains in MYC binding. Altogether, the relative abundance (henceforth, "share") of MYC at promoters was the strongest predictor of transcriptional responses in diverse cell types, predominating over MYC's association with the corepressor ZBTB17 (also known as MIZ1). MYC activation elicited immediate loading of RNA polymerase II (RNAPII) at activated promoters, followed by increases in pause-release, while repressed promoters showed opposite effects. Gains and losses in RNAPII loading were proportional to the changes in the MYC share, suggesting that repression by MYC may be partly indirect, owing to competition for limiting amounts of RNAPII. Secondary to the changes in RNAPII loading, the dynamics of elongation and pre-mRNA processing were also rapidly altered at MYC regulated genes, leading to the transient accumulation of partially or aberrantly processed mRNAs. Altogether, our results shed light on how overexpressed MYC alters the various phases of the RNAPII cycle and the resulting transcriptional response.

LowMACA: exploiting protein family analysis for the identification of rare driver mutations in cancer.

BACKGROUND: The increasing availability of resequencing data has led to a better understanding of the most important genes in cancer development. Nevertheless, the mutational landscape of many tumor types is heterogeneous and encompasses a long tail of potential driver genes that are systematically excluded by currently available methods due to the low frequency of their mutations. We developed LowMACA (Low frequency Mutations Analysis via Consensus Alignment), a method that combines the mutations of various proteins sharing the same functional domains to identify conserved residues that harbor clustered mutations in multiple sequence alignments. LowMACA is designed to visualize and statistically assess potential driver genes through the identification of their mutational hotspots. RESULTS: We analyzed the Ras superfamily exploiting the known driver mutations of the trio K-N-HRAS, identifying new putative driver mutations and genes belonging to less known members of the Rho, Rab and Rheb subfamilies. Furthermore, we applied the same concept to a list of known and candidate driver genes, and observed that low confidence genes show similar patterns of mutation compared to high confidence genes of the same protein family. CONCLUSIONS: LowMACA is a software for the identification of gain-of-function mutations in putative oncogenic families, increasing the amount of information on functional domains and their possible role in cancer. In this context LowMACA emphasizes the role of genes mutated at low frequency otherwise undetectable by classical single gene analysis. LowMACA is an R package available at http://www.bioconductor.org/packages/release/bioc/html/LowMACA.html. It is also available as a GUI standalone downloadable at: https://cgsb.genomics.iit.it/wiki/projects/LowMACA.

Selective transcriptional regulation by Myc: Experimental design and computational analysis of high-throughput sequencing data.

The gene expression programs regulated by the Myc transcription factor were evaluated by integrated genome-wide profiling of Myc binding sites, chromatin marks and RNA expression in several biological models. Our results indicate that Myc directly drives selective transcriptional regulation, which in certain physiological conditions may indirectly lead to RNA amplification. Here, we illustrate in detail the experimental design concerning the high-throughput sequencing data associated with our study (Sabò et al., Nature. (2014) 511:488-492) and the R scripts used for their computational analysis.

Selective transcriptional regulation by Myc in cellular growth control and lymphomagenesis.

The c-myc proto-oncogene product, Myc, is a transcription factor that binds thousands of genomic loci. Recent work suggested that rather than up- and downregulating selected groups of genes, Myc targets all active promoters and enhancers in the genome (a phenomenon termed 'invasion') and acts as a general amplifier of transcription. However, the available data did not readily discriminate between direct and indirect effects of Myc on RNA biogenesis. We addressed this issue with genome-wide chromatin immunoprecipitation and RNA expression profiles during B-cell lymphomagenesis in mice, in cultured B cells and fibroblasts. Consistent with long-standing observations, we detected general increases in total RNA or messenger RNA copies per cell (hereby termed 'amplification') when comparing actively proliferating cells with control quiescent cells: this was true whether cells were stimulated by mitogens (requiring endogenous Myc for a proliferative response) or by deregulated, oncogenic Myc activity. RNA amplification and promoter/enhancer invasion by Myc were separable phenomena that could occur without one another. Moreover, whether or not associated with RNA amplification, Myc drove the differential expression of distinct subsets of target genes. Hence, although having the potential to interact with all active or poised regulatory elements in the genome, Myc does not directly act as a global transcriptional amplifier. Instead, our results indicate that Myc activates and represses transcription of discrete gene sets, leading to changes in cellular state that can in turn feed back on global RNA production and turnover.

DOTS-Finder: a comprehensive tool for assessing driver genes in cancer genomes.

A key challenge in the analysis of cancer genomes is the identification of driver genes from the vast number of mutations present in a cohort of patients. DOTS-Finder is a new tool that allows the detection of driver genes through the sequential application of functional and frequentist approaches, and is specifically tailored to the analysis of few tumor samples. We have identified driver genes in the genomic data of 34 tumor types derived from existing exploratory projects such as The Cancer Genome Atlas and from studies investigating the usefulness of genomic information in the clinical settings. DOTS-Finder is available at https://cgsb.genomics.iit.it/wiki/projects/DOTS-Finder/.