Genetic regulation of m6A RNA methylation and its contribution in human complex diseases.

N6-methyladenosine (m6A) has been established as the most prevalent chemical modification in message RNA (mRNA), playing an essential role in determining the fate of RNA molecules. Dysregulation of m6A has been revealed to lead to abnormal physiological conditions and cause various types of human diseases. Recent studies have delineated the genetic regulatory maps for m6A methylation by mapping the quantitative trait loci of m6A (m6A-QTLs), thereby building up the regulatory circuits linking genetic variants, m6A, and human complex traits. Here, we review the recent discoveries concerning the genetic regulatory maps of m6A, describing the methodological and technical details of m6A-QTL identification, and introducing the key findings of the cis- and trans-acting drivers of m6A. We further delve into the tissue- and ethnicity-specificity of m6A-QTL, the association with other molecular phenotypes in light of genetic regulation, the regulators underlying m6A genetics, and importantly, the functional roles of m6A in mediating human complex diseases. Lastly, we discuss potential research avenues that can accelerate the translation of m6A genetics studies toward the development of therapies for human genetic diseases.

Multitissue H3K27ac profiling of GTEx samples links epigenomic variation to disease.

Genetic variants associated with complex traits are primarily noncoding, and their effects on gene-regulatory activity remain largely uncharacterized. To address this, we profile epigenomic variation of histone mark H3K27ac across 387 brain, heart, muscle and lung samples from Genotype-Tissue Expression (GTEx). We annotate 282 k active regulatory elements (AREs) with tissue-specific activity patterns. We identify 2,436 sex-biased AREs and 5,397 genetically influenced AREs associated with 130 k genetic variants (haQTLs) across tissues. We integrate genetic and epigenomic variation to provide mechanistic insights for disease-associated loci from 55 genome-wide association studies (GWAS), by revealing candidate tissues of action, driver SNPs and impacted AREs. Lastly, we build ARE-gene linking scores based on genetics (gLink scores) and demonstrate their unique ability to prioritize SNP-ARE-gene circuits. Overall, our epigenomic datasets, computational integration and mechanistic predictions provide valuable resources and important insights for understanding the molecular basis of human diseases/traits such as schizophrenia.

Human microglial state dynamics in Alzheimer's disease progression.

Altered microglial states affect neuroinflammation, neurodegeneration, and disease but remain poorly understood. Here, we report 194,000 single-nucleus microglial transcriptomes and epigenomes across 443 human subjects and diverse Alzheimer's disease (AD) pathological phenotypes. We annotate 12 microglial transcriptional states, including AD-dysregulated homeostatic, inflammatory, and lipid-processing states. We identify 1,542 AD-differentially-expressed genes, including both microglia-state-specific and disease-stage-specific alterations. By integrating epigenomic, transcriptomic, and motif information, we infer upstream regulators of microglial cell states, gene-regulatory networks, enhancer-gene links, and transcription-factor-driven microglial state transitions. We demonstrate that ectopic expression of our predicted homeostatic-state activators induces homeostatic features in human iPSC-derived microglia-like cells, while inhibiting activators of inflammation can block inflammatory progression. Lastly, we pinpoint the expression of AD-risk genes in microglial states and differential expression of AD-risk genes and their regulators during AD progression. Overall, we provide insights underlying microglial states, including state-specific and AD-stage-specific microglial alterations at unprecedented resolution.

Epigenomic dissection of Alzheimer's disease pinpoints causal variants and reveals epigenome erosion.

Recent work has identified dozens of non-coding loci for Alzheimer's disease (AD) risk, but their mechanisms and AD transcriptional regulatory circuitry are poorly understood. Here, we profile epigenomic and transcriptomic landscapes of 850,000 nuclei from prefrontal cortexes of 92 individuals with and without AD to build a map of the brain regulome, including epigenomic profiles, transcriptional regulators, co-accessibility modules, and peak-to-gene links in a cell-type-specific manner. We develop methods for multimodal integration and detecting regulatory modules using peak-to-gene linking. We show AD risk loci are enriched in microglial enhancers and for specific TFs including SPI1, ELF2, and RUNX1. We detect 9,628 cell-type-specific ATAC-QTL loci, which we integrate alongside peak-to-gene links to prioritize AD variant regulatory circuits. We report differential accessibility of regulatory modules in late AD in glia and in early AD in neurons. Strikingly, late-stage AD brains show global epigenome dysregulation indicative of epigenome erosion and cell identity loss.

N1-methyladenosine methylation in tRNA drives liver tumourigenesis by regulating cholesterol metabolism.

Hepatocellular carcinoma (HCC) accounts for the majority of primary liver cancers and is characterized by high recurrence and heterogeneity, yet its mechanism is not well understood. Here we show that N1-methyladenosine methylation (m1A) in tRNA is remarkably elevated in hepatocellular carcinoma (HCC) patient tumour tissues. Moreover, m1A methylation signals are increased in liver cancer stem cells (CSCs) and are negatively correlated with HCC patient survival. TRMT6 and TRMT61A, forming m1A methyltransferase complex, are highly expressed in advanced HCC tumours and are negatively correlated with HCC survival. TRMT6/TRMT61A-mediated m1A methylation is required for liver tumourigenesis. Mechanistically, TRMT6/TRMT61A elevates the m1A methylation in a subset of tRNA to increase PPARδ translation, which in turn triggers cholesterol synthesis to activate Hedgehog signaling, eventually driving self-renewal of liver CSCs and tumourigenesis. Finally, we identify a potent inhibitor against TRMT6/TRMT61A complex that exerts effective therapeutic effect on liver cancer.

Genetic drivers of m6A methylation in human brain, lung, heart and muscle.

The most prevalent post-transcriptional mRNA modification, N6-methyladenosine (m6A), plays diverse RNA-regulatory roles, but its genetic control in human tissues remains uncharted. Here we report 129 transcriptome-wide m6A profiles, covering 91 individuals and 4 tissues (brain, lung, muscle and heart) from GTEx/eGTEx. We integrate these with interindividual genetic and expression variation, revealing 8,843 tissue-specific and 469 tissue-shared m6A quantitative trait loci (QTLs), which are modestly enriched in, but mostly orthogonal to, expression QTLs. We integrate m6A QTLs with disease genetics, identifying 184 GWAS-colocalized m6A QTL, including brain m6A QTLs underlying neuroticism, depression, schizophrenia and anxiety; lung m6A QTLs underlying expiratory flow and asthma; and muscle/heart m6A QTLs underlying coronary artery disease. Last, we predict novel m6A regulators that show preferential binding in m6A QTLs, protein interactions with known m6A regulators and expression correlation with the m6A levels of their targets. Our results provide important insights and resources for understanding both cis and trans regulation of epitranscriptomic modifications, their interindividual variation and their roles in human disease.

Landscape and Regulation of m6A and m6Am Methylome across Human and Mouse Tissues.

N6-methyladenosine (m6A), the most abundant internal mRNA modification, and N6,2'-O-dimethyladenosine (m6Am), found at the first-transcribed nucleotide, are two reversible epitranscriptomic marks. However, the profiles and distribution patterns of m6A and m6Am across human and mouse tissues are poorly characterized. Here, we report the m6A and m6Am methylome through profiling of 43 human and 16 mouse tissues and demonstrate strongest tissue specificity for the brain tissues. A small subset of tissue-specific m6A peaks can also readily classify tissue types. The overall m6A and m6Am level is partially correlated with the expression level of their writers and erasers. Additionally, the m6A-containing regions are enriched for SNPs. Furthermore, cross-species analysis revealed that species rather than tissue type is the primary determinant of methylation. Collectively, our study provides an in-depth resource for dissecting the landscape and regulation of the m6A and m6Am epitranscriptomic marks across mammalian tissues.

Perspectives on topology of the human m1A methylome at single nucleotide resolution.

N 1-methyladenosine was recently reported to be a chemical modification in mRNA. However, while we identified hundreds of m1A sites in the human transcriptome in a previous work, others have detected only nine sites in cytosolic and mitochondrial mRNAs. Herein, we provide additional evidence that hundreds of m1A sites are present in the human transcriptome. Moreover, we show that both the improper bioinformatic tools and the poor quality of sequencing data in a previous study led to the failure in identifying the majority of m1A sites. Our analysis hence provides an explanation of the divergence in the prevalence of this newly discovered mRNA mark.

N1-methyladenosine methylome in messenger RNA and non-coding RNA.

Chemical modifications to rRNA, tRNA and mRNA provide a new regulatory layer of gene expression, which is termed as the `epitranscriptome'. N1-methyladenosine (m1A), first characterized more than 50 years ago, is a well-known modification in rRNA and tRNA. m1A in these abundant non-coding RNAs plays important roles in maintaining their biological functions. Recent studies also reveal that m1A is present in both nuclear-encoded and mitochondrial-encoded mRNA and is dynamically regulated by environmental and developmental conditions; m1A is found in a subset of nuclear-encoded long non-coding RNAs as well. Finally, we also discuss the potential challenges of identifying m1A modification in the human transcriptome.

Base-Resolution Mapping Reveals Distinct m1A Methylome in Nuclear- and Mitochondrial-Encoded Transcripts.

Gene expression can be post-transcriptionally regulated via dynamic and reversible RNA modifications. N1-methyladenosine (m1A) is a recently identified mRNA modification; however, little is known about its precise location and biogenesis. Here, we develop a base-resolution m1A profiling method, based on m1A-induced misincorporation during reverse transcription, and report distinct classes of m1A methylome in the human transcriptome. m1A in 5' UTR, particularly those at the mRNA cap, associate with increased translation efficiency. A different, small subset of m1A exhibit a GUUCRA tRNA-like motif, are evenly distributed in the transcriptome, and are dependent on the methyltransferase TRMT6/61A. Additionally, we show that m1A is prevalent in the mitochondrial-encoded transcripts. Manipulation of m1A level via TRMT61B, a mitochondria-localizing m1A methyltransferase, demonstrates that m1A in mitochondrial mRNA interferes with translation. Collectively, our approaches reveal distinct classes of m1A methylome and provide a resource for functional studies of m1A-mediated epitranscriptomic regulation.

Epitranscriptome sequencing technologies: decoding RNA modifications.

In recent years, major breakthroughs in RNA-modification-mediated regulation of gene expression have been made, leading to the emerging field of epitranscriptomics.Our understanding of the distribution, regulation and function of these dynamic RNA modifications is based on sequencing technologies. In this Review, we focus on the major mRNA modifications in the transcriptome of eukaryotic cells: N6-methyladenosine, N6, 2'-O-dimethyladenosine, 5-methylcytidine, 5-hydroxylmethylcytidine, inosine, pseudouridine and N1-methyladenosine. We discuss the sequencing technologies used to profile these epitranscriptomic marks, including scale, resolution, quantitative feature, pre-enrichment capability and the corresponding bioinformatics tools. We also discuss the challenges of epitranscriptome profiling and highlight the prospect of future detection tools. We aim to guide the choice of different detection methods and inspire new ideas in RNA biology.

Base-Resolution Analysis of Cisplatin-DNA Adducts at the Genome Scale.

Cisplatin, one of the most widely used anticancer drugs, crosslinks DNA and ultimately induces cell death. However, the genomic pattern of cisplatin-DNA adducts has remained unknown owing to the lack of a reliable and sensitive genome-wide method. Herein we present "cisplatin-seq" to identify genome-wide cisplatin crosslinking sites at base resolution. Cisplatin-seq reveals that mitochondrial DNA is a preferred target of cisplatin. For nuclear genomes, cisplatin-DNA adducts are enriched within promoters and regions harboring transcription termination sites. While the density of GG dinucleotides determines the initial crosslinking of cisplatin, binding of proteins to the genome largely contributes to the accumulative pattern of cisplatin-DNA adducts.

Transcriptome-wide mapping reveals reversible and dynamic N(1)-methyladenosine methylome.

N(1)-Methyladenosine (m(1)A) is a prevalent post-transcriptional RNA modification, yet little is known about its abundance, topology and dynamics in mRNA. Here, we show that m(1)A is prevalent in Homo sapiens mRNA, which shows an m(1)A/A ratio of ∼0.02%. We develop the m(1)A-ID-seq technique, based on m(1)A immunoprecipitation and the inherent ability of m(1)A to stall reverse transcription, as a means for transcriptome-wide m(1)A profiling. m(1)A-ID-seq identifies 901 m(1)A peaks (from 600 genes) in mRNA and noncoding RNA and reveals a prominent feature, enrichment in the 5' untranslated region of mRNA transcripts, that is distinct from the pattern for N(6)-methyladenosine, the most abundant internal mammalian mRNA modification. Moreover, m(1)A in mRNA is reversible by ALKBH3, a known DNA/RNA demethylase. Lastly, we show that m(1)A methylation responds dynamically to stimuli, and we identify hundreds of stress-induced m(1)A sites. Collectively, our approaches allow comprehensive analysis of m(1)A modification and provide tools for functional studies of potential epigenetic regulation via the reversible and dynamic m(1)A methylation.

Transcription factor and microRNA co-regulatory loops: important regulatory motifs in biological processes and diseases.

Transcription factors (TFs) and microRNAs (miRNAs) can jointly regulate target gene expression in the forms of feed-forward loops (FFLs) or feedback loops (FBLs). These regulatory loops serve as important motifs in gene regulatory networks and play critical roles in multiple biological processes and different diseases. Major progress has been made in bioinformatics and experimental study for the TF and miRNA co-regulation in recent years. To further speed up its identification and functional study, it is indispensable to make a comprehensive review. In this article, we summarize the types of FFLs and FBLs and their identified methods. Then, we review the behaviors and functions for the experimentally identified loops according to biological processes and diseases. Future improvements and challenges are also discussed, which includes more powerful bioinformatics approaches and high-throughput technologies in TF and miRNA target prediction, and the integration of networks of multiple levels.