Single-cell multiplex chromatin and RNA interactions in ageing human brain.

Dynamically organized chromatin complexes often involve multiplex chromatin interactions and sometimes chromatin-associated RNA1-3. Chromatin complex compositions change during cellular differentiation and ageing, and are expected to be highly heterogeneous among terminally differentiated single cells4-7. Here we introduce the multinucleic acid interaction mapping in single cells (MUSIC) technique for concurrent profiling of multiplex chromatin interactions, gene expression and RNA-chromatin associations within individual nuclei. When applied to 14 human frontal cortex samples from older donors, MUSIC delineated diverse cortical cell types and states. We observed that nuclei exhibiting fewer short-range chromatin interactions were correlated with both an 'older' transcriptomic signature and Alzheimer's disease pathology. Furthermore, the cell type exhibiting chromatin contacts between cis expression quantitative trait loci and a promoter tends to be that in which these cis expression quantitative trait loci specifically affect the expression of their target gene. In addition, female cortical cells exhibit highly heterogeneous interactions between XIST non-coding RNA and chromosome X, along with diverse spatial organizations of the X chromosomes. MUSIC presents a potent tool for exploration of chromatin architecture and transcription at cellular resolution in complex tissues.

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.

Effect of single versus grouped culture of human cumulus-oocyte complexes in PCOS women treated with biphasic in vitro maturation: A sibling oocyte pilot study.

Purpose: This study investigated the differences in the maturation rate of single versus grouped cumulus-oocyte complexes (COCs) culture methods for capacitation in vitro maturation (CAPA-IVM) in women with polycystic ovary syndrome (PCOS). Methods: This study was performed at My Duc Phu Nhuan Hospital, Vietnam from October 1, 2020 to October 24, 2021. Women aged 18-37 years with a diagnosis of PCOS were recruited. COCs from each woman were randomly divided into two groups: single or grouped culture during CAPA-IVM culture. The primary outcome was the maturation rate. Results: A total of 322 COCs from 15 eligible women included were randomly assigned to the two study groups. The maturation rate was comparable between the single and grouped culture groups (61.3% vs. 64.8%; p = 0.56). There were no significant differences in the number of 2-pronuclei fertilized oocytes, number of day-3 embryos, and number of good-quality embryos in the two culture method groups. In the single culture group, COCs morphology was associated with the day-3 embryo formation rate but not the maturation rate. Conclusions: Comparable oocyte maturation and embryology outcomes between single and grouped COCs culture utilizing sibling COCs derived from women with PCOS suggest the feasibility of both methods for CAPA-IVM culture.

Cumulative live birth rate after oocyte in vitro maturation with a pre-maturation step in women with polycystic ovary syndrome or high antral follicle count.

PURPOSE: This study evaluated the 24-month cumulative live birth rate (CLBR) for women with polycystic ovary syndrome (PCOS) or high antral follicle count (AFC) who underwent oocyte in vitro maturation (IVM) with pre-maturation step (CAPA-IVM). METHODS: This multicenter, retrospective study was performed at IVFMD, My Duc Hospital, and IVFMD Phu Nhuan, My Duc Phu Nhuan Hospital from 1 January 2017 to 31 December 2019. All women with PCOS or high AFC treated with a CAPA-IVM cycle were included. Cumulative live birth was defined as at least one live birth resulting from the initiated CAPA-IVM cycle. Where a woman did not return for embryo transfer, outcomes were followed up until 24 months from the day of oocyte aspiration. Logistic regression was performed to identify factors predicting the CLBR. RESULTS: Data from 374 women were analyzed, 368 of whom had embryos for transfer (98.4%), and six had no embryos for transfer (1.6%). The oocyte maturation rate was 63.2%. The median number of frozen embryos was 4 [quartile 1, 2; quartile 3, 6]. Cumulative clinical pregnancy and ongoing pregnancy rates were 60.4% and 43.6%, respectively. At 24 months after starting CAPA-IVM treatment, the CLBR was 38.5%. Multivariate analysis showed that patient age and number of frozen embryos were significant predictors of cumulative live birth after CAPA-IVM. CONCLUSIONS: CAPA-IVM could be considered as an alternative to in vitro fertilization for the management of infertility in women with PCOS or a high AFC who require assisted reproductive technology.

RNA, Action through Interactions.

As transcription of the human genome is quite pervasive, it is possible that many novel functions of the noncoding genome have yet to be identified. Often the noncoding genome's functions are carried out by their RNA transcripts, which may rely on their structures and/or extensive interactions with other molecules. Recent technology developments are transforming the fields of RNA biology from studying one RNA at a time to transcriptome-wide mapping of structures and interactions. Here, we highlight the recent advances in transcriptome-wide RNA interaction analysis. These technologies revealed surprising versatility of RNA to participate in diverse molecular systems. For example, tens of thousands of RNA-RNA interactions have been revealed in cultured cells as well as in mouse brain, including interactions between transposon-produced transcripts and mRNAs. In addition, most transcription start sites in the human genome are associated with noncoding RNA transcribed from other genomic loci. These recent discoveries expanded our understanding of RNAs' roles in chromatin organization, gene regulation, and intracellular signaling.

Single-cell multiplex chromatin and RNA interactions in aging human brain.

The dynamically organized chromatin complexes often involve multiplex chromatin interactions and sometimes chromatin-associated RNA (caRNA) 1-3. Chromatin complex compositions change during cellular differentiation and aging, and are expected to be highly heterogeneous among terminally differentiated single cells 4-7. Here we introduce the Multi-Nucleic Acid Interaction Mapping in Single Cell (MUSIC) technique for concurrent profiling of multiplex chromatin interactions, gene expression, and RNA-chromatin associations within individual nuclei. Applied to 14 human frontal cortex samples from elderly donors, MUSIC delineates diverse cortical cell types and states. We observed the nuclei exhibiting fewer short-range chromatin interactions are correlated with an "older" transcriptomic signature and with Alzheimer's pathology. Furthermore, the cell type exhibiting chromatin contacts between cis expression quantitative trait loci (cis eQTLs) and a promoter tends to be the cell type where these cis eQTLs specifically affect their target gene's expression. Additionally, the female cortical cells exhibit highly heterogeneous interactions between the XIST non-coding RNA and Chromosome X, along with diverse spatial organizations of the X chromosomes. MUSIC presents a potent tool for exploring chromatin architecture and transcription at cellular resolution in complex tissues.

Embryological and clinical outcomes in couples with severe male factor infertility versus normozoospermia.

OBJECTIVE: This study evaluated embryological and clinical outcomes in couples with severe male factor infertility versus those with normozoospermia undergoing ICSI and in vitro fertilisation. METHODS: This multicentre, retrospective cohort study included all couples who had undergone autologous ICSI cycles at My Duc Hospital and My Duc Phu Nhuan Hospital in Vietnam between January 2018 and January 2021 (female age < 35 years and males with severe male factor or normozoospermia based on the World Health Organization 2010 criteria). The primary outcome was the cumulative live birth rate after the first ICSI cycle. RESULTS: A total of 1296 couples were included, including 648 with severe male factor infertility and 648 with normozoospermia. The number of two pronuclei zygotes, embryos, and frozen embryos was significantly lower in couples with severe male factor infertility compared with normozoospermia (p < 0.05). In contrast, there were no significant differences between the two groups with respect to cumulative pregnancy outcomes, including the live birth rate, and secondary outcomes including clinical pregnancy rate, ongoing pregnancy rate, and miscarriage rate. CONCLUSION: Severe male factor infertility appeared to have an impact on the fertilisation and early developmental potential of embryos, but sperm quality did not affect cumulative clinical fertility outcomes.

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.

An encyclopedia of enhancer-gene regulatory interactions in the human genome.

Identifying transcriptional enhancers and their target genes is essential for understanding gene regulation and the impact of human genetic variation on disease1-6. Here we create and evaluate a resource of >13 million enhancer-gene regulatory interactions across 352 cell types and tissues, by integrating predictive models, measurements of chromatin state and 3D contacts, and largescale genetic perturbations generated by the ENCODE Consortium7. We first create a systematic benchmarking pipeline to compare predictive models, assembling a dataset of 10,411 elementgene pairs measured in CRISPR perturbation experiments, >30,000 fine-mapped eQTLs, and 569 fine-mapped GWAS variants linked to a likely causal gene. Using this framework, we develop a new predictive model, ENCODE-rE2G, that achieves state-of-the-art performance across multiple prediction tasks, demonstrating a strategy involving iterative perturbations and supervised machine learning to build increasingly accurate predictive models of enhancer regulation. Using the ENCODE-rE2G model, we build an encyclopedia of enhancer-gene regulatory interactions in the human genome, which reveals global properties of enhancer networks, identifies differences in the functions of genes that have more or less complex regulatory landscapes, and improves analyses to link noncoding variants to target genes and cell types for common, complex diseases. By interpreting the model, we find evidence that, beyond enhancer activity and 3D enhancer-promoter contacts, additional features guide enhancerpromoter communication including promoter class and enhancer-enhancer synergy. Altogether, these genome-wide maps of enhancer-gene regulatory interactions, benchmarking software, predictive models, and insights about enhancer function provide a valuable resource for future studies of gene regulation and human genetics.

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.

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.

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.

Mapping RNA-RNA interactome and RNA structure in vivo by MARIO.

The pervasive transcription of our genome presents a possibility of revealing new genomic functions by investigating RNA interactions. Current methods for mapping RNA-RNA interactions have to rely on an 'anchor' protein or RNA and often require molecular perturbations. Here we present the MARIO (Mapping RNA interactome in vivo) technology to massively reveal RNA-RNA interactions from unperturbed cells. We mapped tens of thousands of endogenous RNA-RNA interactions from mouse embryonic stem cells and brain. We validated seven interactions by RNA antisense purification and one interaction using single-molecule RNA-FISH. The experimentally derived RNA interactome is a scale-free network, which is not expected from currently perceived promiscuity in RNA-RNA interactions. Base pairing is observed at the interacting regions between long RNAs, including transposon transcripts, suggesting a class of regulatory sequences acting in trans. In addition, MARIO data reveal thousands of intra-molecule interactions, providing in vivo data on high-order RNA structures.