m6A mRNA methylation facilitates resolution of naïve pluripotency toward differentiation
27 Feb 2015-Science (American Association for the Advancement of Science)-Vol. 347, Iss: 6225, pp 1002-1006
TL;DR: It is shown that N6-methyladenosine (m6A), a messenger RNA (mRNA) modification present on transcripts of pluripotency factors, drives this transition from the pluripotent to the differentiated state.
Abstract: Naive and primed pluripotent states retain distinct molecular properties, yet limited knowledge exists on how their state transitions are regulated. Here, we identify Mettl3, an N(6)-methyladenosine (m(6)A) transferase, as a regulator for terminating murine naive pluripotency. Mettl3 knockout preimplantation epiblasts and naive embryonic stem cells are depleted for m(6)A in mRNAs, yet are viable. However, they fail to adequately terminate their naive state and, subsequently, undergo aberrant and restricted lineage priming at the postimplantation stage, which leads to early embryonic lethality. m(6)A predominantly and directly reduces mRNA stability, including that of key naive pluripotency-promoting transcripts. This study highlights a critical role for an mRNA epigenetic modification in vivo and identifies regulatory modules that functionally influence naive and primed pluripotency in an opposing manner.
Citations
More filters
TL;DR: In a unified mechanism of m(6)A-based regulation in the cytoplasm, YTHDF2-mediated degradation controls the lifetime of target transcripts, whereasYTHDF1-mediated translation promotion increases translation efficiency, ensuring effective protein production from dynamic transcripts that are marked by m( 6)A.
2,179 citations
Cites background from "m6A mRNA methylation facilitates re..."
...…m6A methyltransferase is crucial for yeast meiosis (Shah and Clancy, 1992; Schwartz et al., 2013), the differentiation of mouse embryonic stem cells (Geula et al., 2015; Wang et al., 2014b), the development of fruit flies (Hongay and Orr-Weaver, 2011) and plants (Zhong et al., 2008),…...
[...]
...…human YTH domain proteins that appear to affect mRNA stability (Harigaya et al., 2006; Hiriart et al., 2012; Kang et al., 2014) and the findings that m6A directs the expression of pluripotency regulators in mouse embryonic stem cells (Batista et al., 2014; Geula et al., 2015; Wang et al., 2014b)....
[...]
TL;DR: Roles for mRNA modification in nearly every aspect of the mRNA life cycle, as well as in various cellular, developmental, and disease processes are revealed.
1,855 citations
Cites background from "m6A mRNA methylation facilitates re..."
...Mettl3 / mice are not viable, and cells derived from early embryos are unable to resolve their naive pluripotency due to extended transcript lifetime in the complete absence of methylation (Geula et al., 2015)....
[...]
University of Cincinnati Academic Health Center1, City of Hope National Medical Center2, Sun Yat-sen University3, Howard Hughes Medical Institute4, University of Chicago5, China Medical University (PRC)6, Cincinnati Children's Hospital Medical Center7, Martin Luther University of Halle-Wittenberg8, Zhejiang University9
TL;DR: This work reports the insulin-like growth factor 2 mRNA-binding proteins as a distinct family of m6A readers that target thousands of mRNA transcripts through recognizing the consensus GG(m6A)C sequence, and identifies IGF2BPs as an additional class of N6-methyladenosine (m 6A) reader proteins.
Abstract: N6-methyladenosine (m6A) is the most prevalent modification in eukaryotic messenger RNAs (mRNAs) and is interpreted by its readers, such as YTH domain-containing proteins, to regulate mRNA fate. Here, we report the insulin-like growth factor 2 mRNA-binding proteins (IGF2BPs; including IGF2BP1/2/3) as a distinct family of m6A readers that target thousands of mRNA transcripts through recognizing the consensus GG(m6A)C sequence. In contrast to the mRNA-decay-promoting function of YTH domain-containing family protein 2, IGF2BPs promote the stability and storage of their target mRNAs (for example, MYC) in an m6A-dependent manner under normal and stress conditions and therefore affect gene expression output. Moreover, the K homology domains of IGF2BPs are required for their recognition of m6A and are critical for their oncogenic functions. Thus, our work reveals a different facet of the m6A-reading process that promotes mRNA stability and translation, and highlights the functional importance of IGF2BPs as m6A readers in post-transcriptional gene regulation and cancer biology.
1,373 citations
TL;DR: N6-adenosine methylation directs mRNAs to distinct fates by grouping them for differential processing, translation and decay in processes such as cell differentiation, embryonic development and stress responses.
Abstract: The recent discovery of reversible mRNA methylation has opened a new realm of post-transcriptional gene regulation in eukaryotes. The identification and functional characterization of proteins that specifically recognize RNA N6-methyladenosine (m6A) unveiled it as a modification that cells utilize to accelerate mRNA metabolism and translation. N6-adenosine methylation directs mRNAs to distinct fates by grouping them for differential processing, translation and decay in processes such as cell differentiation, embryonic development and stress responses. Other mRNA modifications, including N1-methyladenosine (m1A), 5-methylcytosine (m5C) and pseudouridine, together with m6A form the epitranscriptome and collectively code a new layer of information that controls protein synthesis.
1,369 citations
TL;DR: The findings provide the direct evidence that m(6)A reader YTHDC1 regulates mRNA splicing through recruiting and modulating pre-mRNA splicing factors for their access to the binding regions of targeted mRNAs.
1,244 citations
Cites background from "m6A mRNA methylation facilitates re..."
...…m6A modifications have been implicated in development (Ping et al., 2014; Wang et al., 2014b), fertility (Zheng et al., 2013), cell reprogramming (Batista et al., 2014; Chen et al., 2015; Geula et al., 2015), yeast meiosis (Schwartz et al., 2013), and circadian period (Fustin et al., 2013)....
[...]
..., 2013), cell reprogramming (Batista et al., 2014; Chen et al., 2015; Geula et al., 2015), yeast meiosis (Schwartz et al....
[...]
References
More filters
TL;DR: Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
Abstract: As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
37,898 citations
TL;DR: The Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure outperforms other aligners by a factor of >50 in mapping speed.
Abstract: Motivation Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. Results To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. Availability and implementation STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.
30,684 citations
TL;DR: EdgeR as mentioned in this paper is a Bioconductor software package for examining differential expression of replicated count data, which uses an overdispersed Poisson model to account for both biological and technical variability and empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference.
Abstract: Summary: It is expected that emerging digital gene expression (DGE) technologies will overtake microarray technologies in the near future for many functional genomics applications. One of the fundamental data analysis tasks, especially for gene expression studies, involves determining whether there is evidence that counts for a transcript or exon are significantly different across experimental conditions. edgeR is a Bioconductor software package for examining differential expression of replicated count data. An overdispersed Poisson model is used to account for both biological and technical variability. Empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference. The methodology can be used even with the most minimal levels of replication, provided at least one phenotype or experimental condition is replicated. The software may have other applications beyond sequencing data, such as proteome peptide count data. Availability: The package is freely available under the LGPL licence from the Bioconductor web site (http://bioconductor.org).
29,413 citations
TL;DR: A new software suite for the comparison, manipulation and annotation of genomic features in Browser Extensible Data (BED) and General Feature Format (GFF) format, which allows the user to compare large datasets (e.g. next-generation sequencing data) with both public and custom genome annotation tracks.
Abstract: Motivation: Testing for correlations between different sets of genomic features is a fundamental task in genomics research. However, searching for overlaps between features with existing webbased methods is complicated by the massive datasets that are routinely produced with current sequencing technologies. Fast and flexible tools are therefore required to ask complex questions of these data in an efficient manner. Results: This article introduces a new software suite for the comparison, manipulation and annotation of genomic features in Browser Extensible Data (BED) and General Feature Format (GFF) format. BEDTools also supports the comparison of sequence alignments in BAM format to both BED and GFF features. The tools are extremely efficient and allow the user to compare large datasets (e.g. next-generation sequencing data) with both public and custom genome annotation tracks. BEDTools can be combined with one another as well as with standard UNIX commands, thus facilitating routine genomics tasks as well as pipelines that can quickly answer intricate questions of large genomic datasets. Availability and implementation: BEDTools was written in C++. Source code and a comprehensive user manual are freely available at http://code.google.com/p/bedtools
18,858 citations
TL;DR: This work presents HTSeq, a Python library to facilitate the rapid development of custom scripts for high-throughput sequencing data analysis, and presents htseq-count, a tool developed with HTSequ that preprocesses RNA-Seq data for differential expression analysis by counting the overlap of reads with genes.
Abstract: Motivation: A large choice of tools exists for many standard tasks in the analysis of high-throughput sequencing (HTS) data. However, once a project deviates from standard workflows, custom scripts are needed. Results: We present HTSeq, a Python library to facilitate the rapid development of such scripts. HTSeq offers parsers for many common data formats in HTS projects, as well as classes to represent data, such as genomic coordinates, sequences, sequencing reads, alignments, gene model information and variant calls, and provides data structures that allow for querying via genomic coordinates. We also present htseq-count, a tool developed with HTSeq that preprocesses RNA-Seq data for differential expression analysis by counting the overlap of reads with genes. Availability and implementation: HTSeq is released as an opensource software under the GNU General Public Licence and available from http://www-huber.embl.de/HTSeq or from the Python Package Index at https://pypi.python.org/pypi/HTSeq. Contact: sanders@fs.tum.de
15,744 citations