Single-nucleus multiomic mapping of m6A methylomes and transcriptomes in native populations of cells with sn-m6A-CT

Mild and ultrafast GLORI enables absolute quantification of m6A methylome from low-input samples

Methods for absolute quantification of N6-methyladenosine (m6A) have emerged as powerful tools in epitranscriptomics. We previously reported GLORI, a chemical-assisted approach to achieve unbiased and precise m6A measurement. However, its lengthy reaction time and severe RNA degradation have limited its applicability, particularly for low-input samples. Here, we present two updated GLORI approaches that are ultrafast, mild and enable absolute m6A quantification from one to two orders of magnitude less than the RNA starting material: GLORI 2.0 is compatible with RNA from ~10,000 cells and enhances sensitivity for both transcriptome-wide and locus-specific m6A detection; GLORI 3.0 further utilizes a reverse transcription-silent carrier RNA to achieve m6A quantification from as low as 500-1,000 cells. Using limited RNA from mouse dorsal hippocampus, we reveal a high modification level in synapse-related gene sets. We envision that the updated GLORI methods will greatly expand the applicability of absolute quantification of m6A in biology.

Advances and applications in single-cell and spatial genomics

The applications of single-cell and spatial technologies in recent times have revolutionized the present understanding of cellular states and the cellular heterogeneity inherent in complex biological systems. These advancements offer unprecedented resolution in the examination of the functional genomics of individual cells and their spatial context within tissues. In this review, we have comprehensively discussed the historical development and recent progress in the field of single-cell and spatial genomics. We have reviewed the breakthroughs in single-cell multi-omics technologies, spatial genomics methods, and the computational strategies employed toward the analyses of single-cell atlas data. Furthermore, we have highlighted the advances made in constructing cellular atlases and their clinical applications, particularly in the context of disease. Finally, we have discussed the emerging trends, challenges, and opportunities in this rapidly evolving field.

RMethyMD: An integrated platform for exploring RNA methylation in pan-cancer via a multiomics analysis

A user-friendly integrated database, RMethyMD (http://www.tmliang.cn/rnamethy), was developed to provide a comprehensive analysis of methylation regulators aimed at facilitating the exploration of molecular features in tumorigenesis and clinical implications in cancer diagnosis and treatment via a multiomics approach. Subsequently, molecular landscapes and a robust constructed m6A-based prognostic model using coxBoost + RSF algorithms in lung cancer highlighted m6A as a suitable marker to guide therapeutic strategy. RMethyMD provides a comprehensive resource and multiomics analysis to explore m6A-based prognostic and clinical values, thereby contributing to aiding personalized cancer therapy.

UDA-seq: universal droplet microfluidics-based combinatorial indexing for massive-scale multimodal single-cell sequencing

The use of single-cell combinatorial indexing sequencing via droplet microfluidics presents an attractive approach for balancing cost, scalability, robustness and accessibility. However, existing methods often require tailored protocols for individual modalities, limiting their automation potential and clinical applicability. To address this, we introduce UDA-seq, a universal workflow that integrates a post-indexing step to enhance throughput and systematically adapt existing droplet-based single-cell multimodal methods. UDA-seq was benchmarked across various tissue and cell types, enabling several common multimodal analyses, including single-cell co-assay of RNA and VDJ, RNA and chromatin, and RNA and CRISPR perturbation. Notably, UDA-seq facilitated the efficient generation of over 100,000 high-quality single-cell datasets from three dozen frozen clinical biopsy specimens within a single-channel droplet microfluidics experiment. Downstream analysis demonstrated the robustness of this approach in identifying rare cell subpopulations associated with clinical phenotypes and exploring the vulnerability of cancer cells.

Morphokinetic Analyses of Fishing Cat-Domestic Cat Interspecies Somatic Cell Nuclear Transfer Embryos Through A Time-Lapse System

A time-lapse live embryo monitoring system provides a powerful approach to recording dynamic developmental events of cultured embryos in detail. By obtaining continuous short-interval images, blastocyst formation can be predicted and embryos can be selected. The objective of this study was to investigate the morphokinetic parameters of fishing cat-domestic cat interspecies somatic cell nuclear transfer (iSCNT) embryos from one-cell to blastocyst stages, and in particular, the cleavage patterns of the first division in iSCNT and IVF embryos, as these play a central role in euploidy. Domestic cat in vitro fertilization (IVF) embryos were set up as controls. The results show that morula and blastocyst development rates were significantly lower in the iSCNT embryos compared to their IVF counterparts. All earlier time points of embryonic development before the onset of blastulation in the iSCNT embryos were significantly delayed when compared with their IVF counterparts. In iSCNT, normal embryos (defined as those that developed to the blastocyst stage) took a longer time to reach the morula stage, and these morulas were more likely to undergo compaction, compared to their arrested embryo counterparts. Direct cleavage in the first division is a morphological aberration, and was seen with greater prevalence in iSCNT embryos than control IVF embryos; these aberrant embryos displayed a significantly lower blastocyst development rate than embryos that had undergone normal cleavage. In conclusion, the morphokinetic parameters of fishing cat-domestic cat iSCNT embryos at early stages could be used to predict their potential for development to the blastocyst stage. A time-lapse imaging system is potentially a powerful tool for selecting early embryos with developmental potential for transfer, and hence, for improving feline iSCNT efficiency.

Statistical modeling of single-cell epitranscriptomics enabled trajectory and regulatory inference of RNA methylation

As a fundamental mechanism for gene expression regulation, post-transcriptional RNA methylation plays versatile roles in various biological processes and disease mechanisms. Recent advances in single-cell technology have enabled simultaneous profiling of transcriptome-wide RNA methylation in thousands of cells, holding the promise to provide deeper insights into the dynamics, functions, and regulation of RNA methylation. However, it remains a major challenge to determine how to best analyze single-cell epitranscriptomics data. In this study, we developed SigRM, a computational framework for effectively mining single-cell epitranscriptomics datasets with a large cell number, such as those produced by the scDART-seq technique from the SMART-seq2 platform. SigRM not only outperforms state-of-the-art models in RNA methylation site detection on both simulated and real datasets but also provides rigorous quantification metrics of RNA methylation levels. This facilitates various downstream analyses, including trajectory inference and regulatory network reconstruction concerning the dynamics of RNA methylation.

Multiomics Research: Principles and Challenges in Integrated Analysis

Multiomics research is a transformative approach in the biological sciences that integrates data from genomics, transcriptomics, proteomics, metabolomics, and other omics technologies to provide a comprehensive understanding of biological systems. This review elucidates the fundamental principles of multiomics, emphasizing the necessity of data integration to uncover the complex interactions and regulatory mechanisms underlying various biological processes. We explore the latest advances in computational methodologies, including deep learning, graph neural networks (GNNs), and generative adversarial networks (GANs), which facilitate the effective synthesis and interpretation of multiomics data. Additionally, this review addresses the critical challenges in this field, such as data heterogeneity, scalability, and the need for robust, interpretable models. We highlight the potential of large language models to enhance multiomics analysis through automated feature extraction, natural language generation, and knowledge integration. Despite the important promise of multiomics, the review acknowledges the substantial computational resources required and the complexity of model tuning, underscoring the need for ongoing innovation and collaboration in the field. This comprehensive analysis aims to guide researchers in navigating the principles and challenges of multiomics research to foster advances in integrative biological analysis.

Emerging interactions between RNA methylation and chromatin architecture

Epitranscriptomics, the study of chemical modifications of RNA molecules, is increasingly recognized as an important component of gene expression regulation. While the majority of research has focused on N6-methyladenosine (m6A) RNA methylation on mRNAs, emerging evidence has revealed that the m6A modification extends beyond mRNAs to include chromatin-associated RNAs (caRNAs). CaRNAs constitute an important class of RNAs characterized by their interaction with the genome and epigenome. These features allow caRNAs to be actively involved in shaping genome organization. In this review, we bring into focus recent findings of the dynamic interactions between caRNAs and chromatin architecture and how RNA methylation impacts caRNAs' function in this interplay. We highlight several enabling techniques, which were critical for genome-wide profiling of caRNAs and their modifications. Given the nascent stage of the field, we emphasize on the need to address critical gaps in study of these modifications in more relevant biological systems. Overall, these exciting progress have expanded the scope and reach of epitranscriptomics, unveiling new mechanisms that underpin the control of gene expression and cellular phenotypes, with potential therapeutic implications.

Nuclear receptor-SINE B1 network modulates expanded pluripotency in blastoids and blastocysts

Embryonic stem cells possess the remarkable ability to self-organize into blastocyst-like structures upon induction. These stem cell-based embryo models serve as invaluable platforms for studying embryogenesis and therapeutic developments. Nevertheless, the specific intrinsic regulators that govern this potential for blastoid formation remain unknown. Here we demonstrate an intrinsic program that plays a crucial role in both blastoids and blastocysts across multiple species. We first establish metrics for grading the resemblance of blastoids to mouse blastocysts, and identify the differential activation of gene regulons involved in lineage specification among various blastoid grades. Notably, abrogation of nuclear receptor subfamily 1, group H, member 2 (Nr1h2) drastically reduces blastoid formation. Nr1h2 activation alone is sufficient to rewire conventional ESC into a distinct pluripotency state, enabling them to form blastoids with enhanced implantation capacity in the uterus and contribute to both embryonic and extraembryonic lineages in vivo. Through integrative multi-omics analyses, we uncover the broad regulatory role of Nr1h2 in the transcriptome, chromatin accessibility and epigenome, targeting genes associated with embryonic lineage and the transposable element SINE-B1. The Nr1h2-centred intrinsic program governs and drives the development of both blastoids and early embryos.

Deciphering tumour microenvironment and elucidating the origin of cancer cells in ovarian clear cell carcinoma

Ovarian clear cell carcinoma (CCC) has an East Asian preponderance. It is associated with endometriosis, a benign condition where endometrial (inner lining of the uterus) tissue is found outside the uterus and on the peritoneal surface, in the abdominal or pelvic space. CCC is relatively more resistant to conventional chemotherapy compared to other ovarian cancer subtypes and is associated with a poorer prognosis. In this study, we recruited and obtained tumour tissues from seven patients across the four stages of CCC. The tumour and the tumour microenvironment (TME) from 7 CCC patients spanning clinical stages 1-4 were transcriptionally profiled using high-resolution scRNA-seq to gain insight into CCC's biological mechanisms. Firstly, we built a scRNA-seq resource for the CCC tumour microenvironment (TME). Secondly, we identified the different cell type proportions and found high levels of immune infiltration in CCC. Thirdly, since CCC is associated with endometriosis, we compared CCC with two publicly available endometriosis scRNA-seq datasets. The CCC malignant cells showed similarities with glandular secretory and ciliated epithelial cells found in endometriosis. Finally, we determined the differences in cell-cell communication between various cell types present in CCC TME and endometriosis conditions to gain insights into the transformations in CCC.

Studying m6A in the brain: a perspective on current methods, challenges, and future directions

A major mechanism of post-transcriptional RNA regulation in cells is the addition of chemical modifications to RNA nucleosides, which contributes to nearly every aspect of the RNA life cycle. N6-methyladenosine (m6A) is a highly prevalent modification in cellular mRNAs and non-coding RNAs, and it plays important roles in the control of gene expression and cellular function. Within the brain, proper regulation of m6A is critical for neurodevelopment, learning and memory, and the response to injury, and m6A dysregulation has been implicated in a variety of neurological disorders. Thus, understanding m6A and how it is regulated in the brain is important for uncovering its roles in brain function and potentially identifying novel therapeutic pathways for human disease. Much of our knowledge of m6A has been driven by technical advances in the ability to map and quantify m6A sites. Here, we review current technologies for characterizing m6A and highlight emerging methods. We discuss the advantages and limitations of current tools as well as major challenges going forward, and we provide our perspective on how continued developments in this area can propel our understanding of m6A in the brain and its role in brain disease.

The rise of epitranscriptomics: recent developments and future directions

The epitranscriptomics field has undergone tremendous growth since the discovery that the RNA N6-methyladenosine (m6A) modification is reversible and is distributed throughout the transcriptome. Efforts to map RNA modifications transcriptome-wide and reshape the epitranscriptome in disease settings have facilitated mechanistic understanding and drug discovery in the field. In this review we discuss recent advancements in RNA modification detection methods and consider how these developments can be applied to gain novel insights into the epitranscriptome. We also highlight drug discovery efforts aimed at developing epitranscriptomic therapeutics for cancer and other diseases. Finally, we consider engineering of the epitranscriptome as an emerging direction to investigate RNA modifications and their causal effects on RNA processing at high specificity.

Emerging Roles of RNA Methylation in Development

ConspectusMore than 170 different types of chemical modifications have been identified on diverse types of RNA, collectively known as the epitranscriptome. Among them, N6-methyladenine (m6A), 5-methylcytosine (m5C), N1-methyladenine (m1A), and N7-methylguanosine (m7G) as the ubiquitous post-transcriptional modification are widely involved in regulating the metabolic processes such as RNA degradation, translation, stability, and export, mediating important physiological and pathological processes such as stress regulation, immune response, development, and tumorigenesis. Recently, the regulatory role of RNA modification during developmental processes is getting more attention. Therefore, the development of low-input even single-cell and high-resolution sequencing technologies is crucial for the exploration of the regulatory roles of RNA modifications in these important biological events of trace samples.This account focuses on the roles of RNA modifications in various developmental processes. We describe the distribution characteristics of various RNA modifications, catalytic enzymes, binding proteins, and the development of sequencing technologies. RNA modification is dynamically reversible, which can be catalyzed by methyltransferases and eliminated by demethylases. RNA m6A is the most abundant post-transcriptional modification on eukaryote mRNA, which is mainly concentrated near the stop codon, and involves in RNA metabolism regulation. RNA m5C, another most studied RNA modification, has been identified in a various of organisms and RNA species, mainly enriched in the regions downstream of translation initiation sites and broadly distributes across the whole coding sequence (CDS) in mammalian mRNAs. RNA m1A, with a lower abundance than m6A, is widely distributed in various RNA types, mainly locates in the 5' untranslated region (5'UTR) of mRNA and regulates translation. RNA m7G, one of the most common RNA modifications in eukaryotes, has been identified at cap regions and internal positions of RNAs and recently gained considerable attention.Thanks to the development of sequencing technology, m6A has been found to regulate the tumorigenic process, including tumor proliferation, invasion, and metastasis by modulating oncogenes and tumor suppressor genes, and affect oocyte maturation and embryonic development through regulating maternal and zygotic genes. m5C related proteins have been identified to participate in embryonic development, plant growth, and neural stem cell differentiation in a m5C dependent manner. m1A also has been revealed to be involved in these developmental processes. m7G dysregulation mainly involves in neurodevelopmental disorders and neurodegenerative diseases.Collectively, we summarized the gradually exhibited roles of RNA methylation during development, and discussed the possibility of RNA modifications as candidate biomarkers and potential therapeutic targets. The technological development is anticipated as the major driving force to expand our knowledge in this field.