The fat mass and obesity associated gene (Fto) regulates activity of the dopaminergic midbrain circuitry

Dopaminergic (DA) signaling governs the control of complex behaviors, and its deregulation has been implicated in a wide range of diseases. Here we demonstrate that inactivation of the Fto gene, encoding a nucleic acid demethylase, impairs dopamine receptor type 2 (D2R) and type 3 (D3R) (collectively, 'D2-like receptor')-dependent control of neuronal activity and behavioral responses. Conventional and DA neuron-specific Fto knockout mice show attenuated activation of G protein-coupled inwardly-rectifying potassium (GIRK) channel conductance by cocaine and quinpirole. Impaired D2-like receptor-mediated autoinhibition results in attenuated quinpirole-mediated reduction of locomotion and an enhanced sensitivity to the locomotor- and reward-stimulatory actions of cocaine. Analysis of global N(6)-methyladenosine (m(6)A) modification of mRNAs using methylated RNA immunoprecipitation coupled with next-generation sequencing in the midbrain and striatum of Fto-deficient mice revealed increased adenosine methylation in a subset of mRNAs important for neuronal signaling, including many in the DA signaling pathway. Several proteins encoded by these mRNAs had altered expression levels. Collectively, FTO regulates the demethylation of specific mRNAs in vivo, and this activity relates to the control of DA transmission

trumpet: transcriptome-guided quality assessment of m(6)A-seq data

Abstract Background Methylated RNA immunoprecipitation sequencing (MeRIP-seq or m6A-seq) has been extensively used for profiling transcriptome-wide distribution of RNA N6-Methyl-Adnosine methylation. However, due to the intrinsic properties of RNA molecules and the intricate procedures of this technique, m6A-seq data often suffer from various flaws. A convenient and comprehensive tool is needed to assess the quality of m6A-seq data to ensure that they are suitable for subsequent analysis. Results From a technical perspective, m6A-seq can be considered as a combination of ChIP-seq and RNA-seq; hence, by effectively combing the data quality assessment metrics of the two techniques, we developed the trumpet R package for evaluation of m6A-seq data quality. The trumpet package takes the aligned BAM files from m6A-seq data together with the transcriptome information as the inputs to generate a quality assessment report in the HTML format. Conclusions The trumpet R package makes a valuable tool for assessing the data quality of m6A-seq, and it is also applicable to other fragmented RNA immunoprecipitation sequencing techniques, including m1A-seq, CeU-Seq, Ψ-seq, etc

Mapping DNA methylation with high-throughput nanopore sequencing

DNA chemical modifications regulate genomic function. We present a framework for mapping cytosine and adenosine methylation with the Oxford Nanopore Technologies MinION using this nanopore sequencer's ionic current signal. We map three cytosine variants and two adenine variants. The results show that our model is sensitive enough to detect changes in genomic DNA methylation levels as a function of growth phase in Escherichia coli

Accurate detection of m6A RNA modifications in native RNA sequences

The epitranscriptomics field has undergone an enormous expansion in the last few years; however, a major limitation is the lack of generic methods to map RNA modifications transcriptome-wide. Here, we show that using direct RNA sequencing, N6-methyladenosine (m6A) RNA modifications can be detected with high accuracy, in the form of systematic errors and decreased base-calling qualities. Specifically, we find that our algorithm, trained with m6A-modified and unmodified synthetic sequences, can predict m6A RNA modifications with ~90% accuracy. We then extend our findings to yeast data sets, finding that our method can identify m6A RNA modifications in vivo with an accuracy of 87%. Moreover, we further validate our method by showing that these 'errors' are typically not observed in yeast ime4-knockout strains, which lack m6A modifications. Our results open avenues to investigate the biological roles of RNA modifications in their native RNA context