INSPEcT: a computational tool to infer mRNA synthesis, processing and degradation dynamics from RNA- and 4sU-seq time course experiments

Pretis, Stefano de; Kress, Theresia R.; Morelli, Marco J.; Melloni, Giorgio; Riva, Laura; Amati, Bruno; Pelizzola, Mattia

doi:10.1093/bioinformatics/btv288

Cited by 61 publications

(90 citation statements)

References 17 publications

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“…Transcript abundance, synthesis and degradation rates were estimated using the INSPEcT package in R 42 . Spearman correlation between samples were visualized using the corrplot package.…”

Section: Methodsmentioning

confidence: 99%

m6A mRNA methylation controls T cell homeostasis by targeting the IL-7/STAT5/SOCS pathways

Tong

Zhu

et al. 2017

Nature

692

820

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N6 -methyladenosine (m6A) is the most common and abundant messenger RNA modification, modulated by ‘writers’, ‘erasers’ and ‘readers’ of this mark 1,2. In vitro data have shown that m6A influences all fundamental aspects of mRNA metabolism, mainly mRNA stability, to determine stem cell fates 3,4. However, its in vivo physiological function in mammals and adult mammalian cells is still unknown. Here we show that deletion of m6A ‘writer’ protein METTL3 in mouse T cells disrupts T cell homeostasis and differentiation. In a lymphopenic mouse adoptive transfer model, naive Mettl3 deficient T cells failed to undergo homeostatic expansion and remarkably remained in the naïve state up through 12 weeks, thereby preventing colitis. Consistent with these observations, the mRNAs of SOCS family genes encoding STAT- signaling inhibitory proteins, Socs1, Socs3 and Cish, were marked by m6A, exhibited slower mRNA decay and increased mRNAs and protein expression levels in Mettl3 deficient naïve T cells. This increased SOCS family activity consequently inhibited IL-7 mediated STAT5 activation and T cell homeostatic proliferation and differentiation. We also found that m6A plays important roles for inducible degradation of Socs mRNAs in response to IL-7 signaling in order to reprogram Naïve T cells for proliferation and differentiation. Our study elucidates for the first time the in vivo biological role of m6A modification in T cell mediated pathogenesis and reveals a novel mechanism of T cell homeostasis and signal-dependent induction of mRNA degradation.

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“…Transcript abundance, synthesis and degradation rates were estimated using the INSPEcT package in R 42 . Spearman correlation between samples were visualized using the corrplot package.…”

Section: Methodsmentioning

confidence: 99%

m6A mRNA methylation controls T cell homeostasis by targeting the IL-7/STAT5/SOCS pathways

Tong

Zhu

et al. 2017

Nature

692

820

View full text Add to dashboard Cite

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“…Next, we sought to determine transcription rates (k 1 ) of pri-miRNAs by combining nascent RNA sequencing data obtained by short "pulse labeling" (10 ′ 4sU) with the INSPEcT bioinformatic tool (de Pretis et al 2015). We manually defined genomic boundaries of primiRNAs in growing 3T9 fibroblasts according to a combination of 4sU-RNAseq and ChIP-seq (POL2 and H3K4me3) tracks, which mark the transcriptional unit and the promoter region, respectively (Supplemental Fig.…”

Section: Genome-wide Analysis Of Mirna Degradation Rates In Growing Fmentioning

confidence: 99%

Degradation dynamics of microRNAs revealed by a novel pulse-chase approach

et al. 2016

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The regulation of miRNAs is critical to the definition of cell identity and behavior in normal physiology and disease. To date, the dynamics of miRNA degradation and the mechanisms involved in remain largely obscure, in particular, in higher organisms. Here, we developed a pulse-chase approach based on metabolic RNA labeling to calculate miRNA decay rates at genome-wide scale in mammalian cells. Our analysis revealed heterogeneous miRNA half-lives, with many species behaving as stable molecules (T 1/2 > 24 h), while others, including passenger miRNAs and a number (25/129) of guide miRNAs, are quickly turned over (T 1/2 = 4-14 h). Decay rates were coupled with other features, including genomic organization, transcription rates, structural heterogeneity (isomiRs), and target abundance, measured through quantitative experimental approaches. This comprehensive analysis highlighted functional mechanisms that mediate miRNA degradation, as well as the importance of decay dynamics in the regulation of the miRNA pool under both steady-state conditions and during cell transitions.

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“…2A). Integrative analysis of nascent and total RNA-seq time-courses was performed with INSPEcT, a tool that we previously developed (de Pretis et al 2015) to determine the rates of RNA synthesis (i.e., transcription), processing, and degradation (henceforth, "kinetic rates") (Fig. 2B).…”

Section: Alterations Of Transcriptional Dynamics Upon Myc Activationmentioning

confidence: 99%

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

et al. 2017

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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.[Supplemental material is available for this article.]The MYC transcription factor is overexpressed and acts as an oncogenic driver in numerous tumor types. Shedding light on the transcriptional programs driven by MYC is thus a critical area of investigation, with important translational implications. Indeed, numerous studies focused on the analysis of MYC-induced transcriptional responses, typically measuring its binding through ChIP-seq and profiling transcriptional maps by RNA-seq . A series of papers proposed that, rather than acting as a gene-specific regulator, MYC acts as a general amplifier of transcriptional activity (Lin et al. 2012;Nie et al. 2012). However, our re-analysis of the available data led us to reconsider this model and to conclude that the primary activity of MYC lies in the up-and down-regulation of selected sets of genes, RNA "amplification"-when occurring-being best explained as a secondary consequence (Sabò et al. 2014;Walz et al. 2014;Kress et al. 2015Kress et al. , 2016.At the mechanistic level, how MYC activates and represses transcription remains to be largely addressed. In particular, a unifying view on the role of MYC in the recruitment and progression of RNA polymerase II (RNAPII) within the transcriptional units of regulated genes and the consequent dynamics of transcriptiona...

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INSPEcT: a computational tool to infer mRNA synthesis, processing and degradation dynamics from RNA- and 4sU-seq time course experiments

Abstract: Supplementary data are available at Bioinformatics online.

Cited by 61 publications

References 17 publications

m6A mRNA methylation controls T cell homeostasis by targeting the IL-7/STAT5/SOCS pathways

m6A mRNA methylation controls T cell homeostasis by targeting the IL-7/STAT5/SOCS pathways

Degradation dynamics of microRNAs revealed by a novel pulse-chase approach

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

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