Revealing protein-protein interactions at the transcriptome scale by sequencing.

We describe PROPER-seq (protein-protein interaction sequencing) to map protein-protein interactions (PPIs) en masse. PROPER-seq first converts transcriptomes of input cells into RNA-barcoded protein libraries, in which all interacting protein pairs are captured through nucleotide barcode ligation, recorded as chimeric DNA sequences, and decoded at once by sequencing and mapping. We applied PROPER-seq to human embryonic kidney cells, T lymphocytes, and endothelial cells and identified 210,518 human PPIs (collected in the PROPER v.1.0 database). Among these, 1,365 and 2,480 PPIs are supported by published co-immunoprecipitation (coIP) and affinity purification-mass spectrometry (AP-MS) data, 17,638 PPIs are predicted by the prePPI algorithm without previous experimental validation, and 100 PPIs overlap human synthetic lethal gene pairs. In addition, four previously uncharacterized interaction partners with poly(ADP-ribose) polymerase 1 (PARP1) (a critical protein in DNA repair) known as XPO1, MATR3, IPO5, and LEO1 are validated in vivo. PROPER-seq presents a time-effective technology to map PPIs at the transcriptome scale, and PROPER v.1.0 provides a rich resource for studying PPIs.

Extracellular RNA in a single droplet of human serum reflects physiologic and disease states.

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.

Genome-wide colocalization of RNA-DNA interactions and fusion RNA pairs.

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.

Linc2GO: a human LincRNA function annotation resource based on ceRNA hypothesis.

UNLABELLED: Large numbers of long intergenic non-coding RNA (lincRNA) have been detected through high-throughput sequencing technology. However, currently we still know very little about their functions. Therefore, a lincRNA function annotation database is needed to facilitate the study in this field. In this article, we present Linc2GO, a web resource that aims to provide comprehensive functional annotations for human lincRNA. MicroRNA-mRNA and microRNA-lincRNA interaction data were integrated to generate lincRNA functional annotations based on the 'competing endogenous RNA hypothesis'. To the best of our knowledge, Linc2GO is the first database that makes use of the 'competing endogenous RNA hypothesis' to predict lincRNA functions. AVAILABILITY: Freely available at http://www.bioinfo.tsinghua.edu.cn/~liuke/Linc2GO/index.html

A temporal extracellular transcriptome atlas of human pre-implantation development.

Non-invasively evaluating gene expression products in human pre-implantation embryos remains a significant challenge. Here, we develop a non-invasive method for comprehensive characterization of the extracellular RNAs (exRNAs) in a single droplet of spent media that was used to culture human in vitro fertilization embryos. We generate the temporal extracellular transcriptome atlas (TETA) of human pre-implantation development. TETA consists of 245 exRNA sequencing datasets for five developmental stages. These data reveal approximately 4,000 exRNAs at each stage. The exRNAs of the developmentally arrested embryos are enriched with the genes involved in negative regulation of the cell cycle, revealing an exRNA signature of developmental arrest. Furthermore, a machine-learning model can approximate the morphology-based rating of embryo quality based on the exRNA levels. These data reveal the widespread presence of coding gene-derived exRNAs at every stage of human pre-implantation development, and these exRNAs provide rich information on the physiology of the embryo.

Genome-wide analysis of the interplay between chromatin-associated RNA and 3D genome organization in human cells.

The interphase genome is dynamically organized in the nucleus and decorated with chromatin-associated RNA (caRNA). It remains unclear whether the genome architecture modulates the spatial distribution of caRNA and vice versa. Here, we generate a resource of genome-wide RNA-DNA and DNA-DNA contact maps in human cells. These maps reveal the chromosomal domains demarcated by locally transcribed RNA, hereafter termed RNA-defined chromosomal domains. Further, the spreading of caRNA is constrained by the boundaries of topologically associating domains (TADs), demonstrating the role of the 3D genome structure in modulating the spatial distribution of RNA. Conversely, stopping transcription or acute depletion of RNA induces thousands of chromatin loops genome-wide. Activation or suppression of the transcription of specific genes suppresses or creates chromatin loops straddling these genes. Deletion of a specific caRNA-producing genomic sequence promotes chromatin loops that straddle the interchromosomal target sequences of this caRNA. These data suggest a feedback loop where the 3D genome modulates the spatial distribution of RNA, which in turn affects the dynamic 3D genome organization.

A novel differential diagnostic model based on multiple biological parameters for immunoglobulin A nephropathy.

BACKGROUND: Immunoglobulin A nephropathy (IgAN) is the most common form of glomerulonephritis in China. An accurate diagnosis of IgAN is dependent on renal biopsies, and there is lack of non-invasive and practical classification methods for discriminating IgAN from other primary kidney diseases. The objective of this study was to develop a classification model for the auxiliary diagnosis of IgAN using multiparameter analysis with various biological parameters. METHODS: To establish an optimal classification model, 121 cases (58 IgAN vs. 63 non-IgAN) were recruited and statistically analyzed. The model was then validated in another 180 cases. RESULTS: Of the 57 biological parameters, there were 16 parameters that were significantly different (P < 0.05) between IgAN and non-IgAN. The combination of fibrinogen, serum immunoglobulin A level, and manifestation was found to be significant in predicting IgAN. The validation accuracies of the logistic regression and discriminant analysis models were 77.5 and 77.0%, respectively at a predictive probability cut-off of 0.5, and 81.1 and 79.9%, respectively, at a predictive probability cut-off of 0.40. When the predicted probability of the equation containing the combination of fibrinogen, serum IgA level, and manifestation was more than 0.59, a patient had at least an 85.0% probability of having IgAN. When the predicted probability was lower than 0.26, a patient had at least an 88.5% probability of having non-IgAN. The results of the net reclassification improvement certificated serum Immunoglobulin A and fibrinogen had classification power for discriminating IgAN from non-IgAN. CONCLUSIONS: These models possess potential clinical applications in distinguishing IgAN from other primary kidney diseases.

PHGDH expression increases with progression of Alzheimer's disease pathology and symptoms.

Chen et al. reveal an increase of phosphoglycerate dehydrogenase (PHGDH) mRNA and protein levels in two mouse models and four human cohorts in Alzheimer's disease brains compared to age- and sex-matched control brains. The increase of PHGDH expression in human brain correlates with symptomatic development and disease pathology.

Presymptomatic Increase of an Extracellular RNA in Blood Plasma Associates with the Development of Alzheimer's Disease.

The extracellular RNAs (exRNAs) from human biofluid have recently been systematically characterized. However, the correlations of biofluid exRNA levels and human diseases remain largely untested. Here, considering the unmet need for presymptomatic biomarkers of sporadic Alzheimer's disease (AD), we leveraged the recently developed SILVER-seq (small-input liquid volume extracellular RNA sequencing) technology to generate exRNA profiles from a longitudinal collection of human plasma samples. These 164 plasma samples were collected from research subjects 70 years or older with up to 15 years of clinical follow-up prior to death and whose clinical diagnoses were confirmed by pathological analysis of their post mortem brains. The exRNAs of AD-activated genes and transposons in the brain exhibited a concordant trend of increase in AD plasma in comparison with age-matched control plasma. However, when we required statistical significance with multiple testing adjustments, phosphoglycerate dehydrogenase (PHGDH) was the only gene that exhibited consistent upregulation in AD brain transcriptomes from 3 independent cohorts and an increase in AD plasma as compared to controls. We validated PHGDH's serum exRNA and brain protein expression increases in AD by using 5 additional published cohorts. Finally, we compared the time-course exRNA trajectories between "converters" and controls. Plasma PHGDH exRNA exhibited presymptomatic increases in each of the 11 converters during their transitions from normal to cognitive impairment but remained stable over the entire follow-up period in 8 out of the 9 control elderly subjects. These data suggest the potential utilities of plasma exRNA levels for screening and longitudinal exRNA changes as a presymptomatic indication of sporadic AD.

Natural display of nuclear-encoded RNA on the cell surface and its impact on cell interaction.

BACKGROUND: Compared to proteins, glycans, and lipids, much less is known about RNAs on the cell surface. We develop a series of technologies to test for any nuclear-encoded RNAs that are stably attached to the cell surface and exposed to the extracellular space, hereafter called membrane-associated extracellular RNAs (maxRNAs). RESULTS: We develop a technique called Surface-seq to selectively sequence maxRNAs and validate two Surface-seq identified maxRNAs by RNA fluorescence in situ hybridization. To test for cell-type specificity of maxRNA, we use antisense oligos to hybridize to single-stranded transcripts exposed on the surface of human peripheral blood mononuclear cells (PBMCs). Combining this strategy with imaging flow cytometry, single-cell RNA sequencing, and maxRNA sequencing, we identify monocytes as the major type of maxRNA+ PBMCs and prioritize 11 candidate maxRNAs for functional tests. Extracellular application of antisense oligos of FNDC3B and CTSS transcripts inhibits monocyte adhesion to vascular endothelial cells. CONCLUSIONS: Collectively, these data highlight maxRNAs as functional components of the cell surface, suggesting an expanded role for RNA in cell-cell and cell-environment interactions.

Attenuation of epigenetic regulator SMARCA4 and ERK-ETS signaling suppresses aging-related dopaminergic degeneration.

How complex interactions of genetic, environmental factors and aging jointly contribute to dopaminergic degeneration in Parkinson's disease (PD) is largely unclear. Here, we applied frequent gene co-expression analysis on human patient substantia nigra-specific microarray datasets to identify potential novel disease-related genes. In vivo Drosophila studies validated two of 32 candidate genes, a chromatin-remodeling factor SMARCA4 and a biliverdin reductase BLVRA. Inhibition of SMARCA4 was able to prevent aging-dependent dopaminergic degeneration not only caused by overexpression of BLVRA but also in four most common Drosophila PD models. Furthermore, down-regulation of SMARCA4 specifically in the dopaminergic neurons prevented shortening of life span caused by α-synuclein and LRRK2. Mechanistically, aberrant SMARCA4 and BLVRA converged on elevated ERK-ETS activity, attenuation of which by either genetic or pharmacological manipulation effectively suppressed dopaminergic degeneration in Drosophila in vivo. Down-regulation of SMARCA4 or drug inhibition of MEK/ERK also mitigated mitochondrial defects in PINK1 (a PD-associated gene)-deficient human cells. Our findings underscore the important role of epigenetic regulators and implicate a common signaling axis for therapeutic intervention in normal aging and a broad range of age-related disorders including PD.

Mapping RNA-chromatin interactions by sequencing with iMARGI.

RNA-chromatin interactions represent an important aspect of the transcriptional regulation of genes and transposable elements. However, analyses of chromatin-associated RNAs (caRNAs) are often limited to one caRNA at a time. Here, we describe the iMARGI (in situ mapping of RNA-genome interactome) technique, which is 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, iMARGI-Docker, is provided to decode the paired-end sequencing data into caRNA-DNA interactions. Compared to its predecessor MARGI (mapping RNA-genome interactions), the number of input cells for iMARGI is 3-5 million (a 100-fold reduction), experimental time is reduced, and clear checkpoints have been established. It takes a few hours a day and a total of 8 d to complete the construction of an iMARGI sequencing library and 1 d to carry out data processing with iMARGI-Docker.

GIVE: portable genome browsers for personal websites.

Growing popularity and diversity of genomic data demand portable and versatile genome browsers. Here, we present an open source programming library called GIVE that facilitates the creation of personalized genome browsers without requiring a system administrator. By inserting HTML tags, one can add to a personal webpage interactive visualization of multiple types of genomics data, including genome annotation, "linear" quantitative data, and genome interaction data. GIVE includes a graphical interface called HUG (HTML Universal Generator) that automatically generates HTML code for displaying user chosen data, which can be copy-pasted into user's personal website or saved and shared with collaborators. GIVE is available at: https://www.givengine.org/ .

RNAs as Proximity-Labeling Media for Identifying Nuclear Speckle Positions Relative to the Genome.

It remains challenging to identify all parts of the nuclear genome that are in proximity to nuclear speckles, due to physical separation between the nuclear speckle cores and chromatin. We hypothesized that noncoding RNAs including small nuclear RNA (snRNAs) and Malat1, which accumulate at the periphery of nuclear speckles (nsaRNA [nuclear speckle-associated RNA]), may extend to sufficient proximity to the genome. Leveraging a transcriptome-genome interaction assay (mapping of RNA-genome interactions [MARGI]), we identified clusters of nsaRNA-interacting genomic sequences (nsaPeaks). Posttranscriptional pre-mRNAs, which also accumulate to nuclear speckles, exhibited proximity to nsaPeaks but rarely to other genomic regions. Our combined DNA fluorescence in situ hybridization and immunofluorescence analysis in 182 single cells revealed a 3-fold increase in odds for nuclear speckles to localize near an nsaPeak than its neighboring genomic sequence. These data suggest a model that nsaRNAs are located in sufficient proximity to the nuclear genome and leave identifiable genomic footprints, thus revealing the parts of genome proximal to nuclear speckles.

txCoords: A Novel Web Application for Transcriptomic Peak Re-Mapping.

Since the development of new technologies such as RIP-Seq and m6A-seq, peak calling has become an important step in transcriptomic sequencing data analysis. However, many of the reported genomic coordinates of transcriptomic peaks are incorrect owing to negligence of the introns. There is currently a lack of a convenient tool to address this problem. Here, we present txCoords, a novel and easy-to-use web application for transcriptomic peak re-mapping. txCoords can be used to correct the incorrectly reported transcriptomic peaks and retrieve the true sequences. It also supports visualization of the re-mapped peaks in a schematic figure or from the UCSC Genome Browser. Our web server is freely available at http://www.bioinfo.tsinghua.edu.cn/txCoords.

Inhibition of the Hedgehog signaling pathway suppresses cell proliferation by regulating the Gli2/miR-124/AURKA axis in human glioma cells.

Multiple lines of evidence indicate that aberrant activation of Hedgehog (Hh) signaling plays an important role in tumorigenesis in human glioma. However, the underlying molecular mechanism and crucial downstream targets of glioma-associated oncogene (Gli), a primary transcriptional regulator of Hh signaling, are not fully understood. Here, we report the identification of miR-124 as a novel downstream target of the transcriptional factor Gli2, which is important for proliferation and tumor growth in human glioma cells. Blockade of Hh signaling leads to a remarkable increase in miR-124 expression in glioma cells, whereas overexpression of Gli2 suppresses miR-124 expression by increasing the direct binding of Gli2 to the upstream region of the transcriptional start site for miR-124. Furthermore, we found that miR-124 potentially interacts with the 3'-UTR region of AURKA. Overexpression of miR-124 significantly decreased the expression of AURKA in glioma cells. In contrast, the loss of miR-124 led to the increased expression of AURKA mRNA and protein. In addition, cell proliferation and colony formation ability were significantly decreased following Gli2 knockdown in human glioma cells, while transfection with a miR-124 inhibitor rescued the proliferative ability of cells. These results demonstrate that miR-124 is an important downstream target gene of Hh signaling, and the Gli2/miR-124/AURKA axis is essential for the proliferation and growth of human glioma cells.

Systematic Mapping of RNA-Chromatin Interactions In Vivo.

RNA molecules can attach to chromatin. It remains difficult to know what RNAs are associated with chromatin and where the genomic target loci of these RNAs are. 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 a sequencing library for paired-end sequencing. Using MARGI, we produced RNA-genome interaction maps for human embryonic stem cells (ESCs) and human embryonic kidney (HEK) cells. MARGI revealed hundreds of caRNAs, including previously known XIST, SNHG1, NEAT1, and 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 ESCs 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. Chromatin-immunoprecipitation-sequencing (ChIP-seq)-reported H3K27ac and H3K4me3 levels are positively correlated, 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.