Summary RNA molecules can attach to chromatin. It remains difficult to know what RNAs are associated with chromatin and where are the genomic target loci of these RNAs. Here, we present MARGI (Mapping RNA-genome interactions), a technology to massively reveal native RNA-chromatin interactions from unperturbed cells. The gist of this technology is to ligate chromatin associated RNAs (caRNAs) with their target genomic sequences by proximity ligation, forming RNA-DNA chimeric sequences, which are converted to sequencing library for paired-end sequencing. Using MARGI, we produced RNA-genome interaction maps for human embryonic stem (ES) cells and HEK cells. MARGI revealed hundreds of caRNAs including previously known XIST, SNHG1, NEAT1, MALAT1, as well as each caRNA's genomic interaction loci. Using a cross-species experiment, we estimated that approximately 2.2% of MARGI identified interactions were false positives. In ES and HEK cells, the RNA ends of more than 5% of MARGI read pairs were mapped to distal or inter-chromosomal locations as compared to the locations of their corresponding DNA ends. The majority of transcription start sites are associated with distal or inter-chromosomal caRNAs. ChIP-seq reported H3K27ac and H3K4me3 levels are positively while H3K9me3 is negatively correlated with MARGI reported RNA attachment levels. The MARGI technology should facilitate revealing novel RNA functions and their genomic target regions.

SummaryRNA molecules can attach to chromatin. It remains difficult to know what RNAs are associated with chromatin and where are the genomic target loci of these RNAs. Here, we present MARGI (Mapping RNA-genome interactions), a technology to massively reveal native RNA-chromatin interactions from unperturbed cells. The gist of this technology is to ligate chromatin associated RNAs (caRNAs) with their target genomic sequences by proximity ligation, forming RNA-DNA chimeric sequences, which are converted to sequencing library for paired-end sequencing. Using MARGI, we produced RNA-genome interaction maps for human embryonic stem (ES) cells and HEK cells. MARGI revealed hundreds of caRNAs including previously known XIST, SNHG1, NEAT1, MALAT1, as well as each caRNA's genomic interaction loci. Using a cross-species experiment, we estimated that approximately 2.2% of MARGI identified interactions were false positives. In ES and HEK cells, the RNA ends of more than 5% of MARGI read pairs were mapped to distal or inter-chromosomal locations as compared to the locations of their corresponding DNA ends. The majority of transcription start sites are associated with distal or inter-chromosomal caRNAs. ChIP-seq reported H3K27ac and H3K4me3 levels are positively while H3K9me3 is negatively correlated with MARGI reported RNA attachment levels. The MARGI technology should facilitate revealing novel RNA functions and their genomic target regions. Graphical abstractSridhar et al. develop a technology to map global RNA-chromatin interactions in unperturbed cells. They discover hundreds of chromatin associated RNAs. They find that the majority of Correspondence to: Sheng Zhong. 3 Co-first author 4 Lead Contact Supplemental Information: Supplemental Information includes Supplemental Experimental Procedures and four figures and can be found with this article online. All sequencing data are available at Gene Expression Omnibus with access number GSE92345.Author Contributions: B.S., T.C.N., and S.Z. designed the experiments. B.S., T.C.N., and L.H performed the experiments. All authors analyzed and interpreted the data.Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. HHS Public Access Results and Discussion Development of the MARGI technologyWe developed MARGI (Mapping RNA-genome interactions), a technology to massively reveal RNA-chromatin interactions from unperturbed cells. MARGI simultaneously identifies all caRNAs and the respective genomic target loci of each caRNA. This changes the paradigm of analyzing one-RNA-at-a-time, and enables the mapping of the native RNAchromatin interaction netwo...

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Fusion transcripts are used as biomarkers in companion diagnoses. Although more than 15,000 fusion RNAs have been identified from diverse cancer types, few common features have been reported. Here, we compared 16,410 fusion transcripts detected in cancer (from a published cohort of 9,966 tumor samples of 33 cancer types) with genome-wide RNA–DNA interactions mapped in two normal, noncancerous cell types [using iMARGI, an enhanced version of the mapping of RNA–genome interactions (MARGI) assay]. Among the top 10 most significant RNA–DNA interactions in normal cells, 5 colocalized with the gene pairs that formed fusion RNAs in cancer. Furthermore, throughout the genome, the frequency of a gene pair to exhibit RNA–DNA interactions is positively correlated with the probability of this gene pair to present documented fusion transcripts in cancer. To test whether RNA–DNA interactions in normal cells are predictive of fusion RNAs, we analyzed these in a validation cohort of 96 lung cancer samples using RNA sequencing (RNA-seq). Thirty-seven of 42 fusion transcripts in the validation cohort were found to exhibit RNA–DNA interactions in normal cells. Finally, by combining RNA-seq, single-molecule RNA FISH, and DNA FISH, we detected a cancer sample with EML4-ALK fusion RNA without forming the EML4-ALK fusion gene. Collectively, these data suggest an RNA-poise model, where spatial proximity of RNA and DNA could poise for the creation of fusion transcripts.

RNA-chromatin interactions represent an important aspect of transcriptional regulation of genes and transposable elements. However, analyses of chromatin-associated RNAs (caRNA) are often limited to one caRNA at a time. Here, we describe the iMARGI (in situ Mapping of RNA-Genome jnteractome) technique used to discover caRNAs and reveal their respective genomic interaction loci. iMARGI starts with in situ crosslinking and genome fragmentation, followed by converting each proximal RNA-DNA pair into an RNA-linker-DNA chimeric sequence. These chimeric sequences are subsequently converted into a sequencing library suitable for paired-end sequencing. A standardized bioinformatic software package called iMARGI-Docker is provided to decode the paired-end sequencing data into caRNA-DNA interactions (https://sysbio.ucsd.edu/ imargi_pipeline). Compared to its predecessor MARGI, in iMARGI the number of input cells is 3-5 million, which is reduced by 100-fold, experimental time is reduced, and clear checkpoints have been established. It takes a few hours a day and a total of 8 days to complete the construction of an iMARGI sequencing library and one day to carry out data processing with iMARGI-Docker.

Extracellular RNAs (exRNAs) are present in human serum. It remains unclear to what extent these circulating exRNAs may reflect human physiologic and disease states. Here, we developed SILVER-seq (Small Input Liquid Volume Extracellular RNA Sequencing) to efficiently sequence both integral and fragmented exRNAs from a small droplet (5 μL to 7 μL) of liquid biopsy. We calibrated SILVER-seq in reference to other RNA sequencing methods based on milliliters of input serum and quantified droplet-to-droplet and donor-to-donor variations. We carried out SILVER-seq on more than 150 serum droplets from male and female donors ranging from 18 y to 48 y of age. SILVER-seq detected exRNAs from more than a quarter of the human genes, including small RNAs and fragments of mRNAs and long noncoding RNAs (lncRNAs). The detected exRNAs included those derived from genes with tissue (e.g., brain)-specific expression. The exRNA expression levels separated the male and female samples and were correlated with chronological age. Noncancer and breast cancer donors exhibited pronounced differences, whereas donors with or without cancer recurrence exhibited moderate differences in exRNA expression patterns. Even without using differentially expressed exRNAs as features, nearly all cancer and noncancer samples and a large portion of the recurrence and nonrecurrence samples could be correctly classified by exRNA expression values. These data suggest the potential of using exRNAs in a single droplet of serum for liquid biopsy-based diagnostics.

N6-Methyladenosine (m6A) is the most common mRNA modification; it occurs in a wide range of taxon and is associated with many key biological processes. High-throughput experiments have identified m6A-peaks and sites across the transcriptome, but studies of m6A sites at the transcriptome-wide scale are limited to a few species and tissue types. Therefore, the computational prediction of mRNA m6A sites has become an important strategy. In this study, we integrated multiple features of mRNA (flanking sequences, local secondary structure information, and relative position information) and trained a SVM classifier to predict m6A sites in mammalian mRNA sequences. Our method achieves ideal performance in both cross-validation tests and rigorous independent dataset tests. The server also provides a comprehensive database of predicted transcriptome-wide m6A sites and curated m6A-seq peaks from the literature for both human and mouse, and these can be queried and visualized in a genome browser. The RNAMethPre web server provides a user-friendly tool for the prediction and query of mRNA m6A sites, which is freely accessible for public use at http://bioinfo.tsinghua.edu.cn/RNAMethPre/index.html.

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