Single-cell multiomics sequencing reveals the functional regulatory landscape of early embryos

Dynamic DNA 5-hydroxylmethylcytosine and RNA 5-methycytosine Reprogramming During Early Human Development

After implantation, complex and highly specialized molecular events render functionally distinct organ formation, whereas how the epigenome shapes organ-specific development remains to be fully elucidated. Here, nano-hmC-Seal, RNA bisulfite sequencing (RNA-BisSeq), and RNA sequencing (RNA-Seq) were performed, and the first multilayer landscapes of DNA 5-hydroxymethylcytosine (5hmC) and RNA 5-methylcytosine (m5C) epigenomes were obtained in the heart, kidney, liver, and lung of the human foetuses at 13-28 weeks with 123 samples in total. We identified 70,091 and 503 organ- and stage-specific differentially hydroxymethylated regions (DhMRs) and m5C-modified mRNAs, respectively. The key transcription factors (TFs), T-box transcription factor 20 (TBX20), paired box 8 (PAX8), krueppel-like factor 1 (KLF1), transcription factor 21 (TCF21), and CCAAT enhancer binding protein beta (CEBPB), specifically contribute to the formation of distinct organs at different stages. Additionally, 5hmC-enriched Alu elements may participate in the regulation of expression of TF-targeted genes. Our integrated studies reveal a putative essential link between DNA modification and RNA methylation, and illustrate the epigenetic maps during human foetal organogenesis, which provide a foundation for for an in-depth understanding of the epigenetic mechanisms underlying early development and birth defects.

Methods and applications for single-cell and spatial multi-omics

The joint analysis of the genome, epigenome, transcriptome, proteome and/or metabolome from single cells is transforming our understanding of cell biology in health and disease. In less than a decade, the field has seen tremendous technological revolutions that enable crucial new insights into the interplay between intracellular and intercellular molecular mechanisms that govern development, physiology and pathogenesis. In this Review, we highlight advances in the fast-developing field of single-cell and spatial multi-omics technologies (also known as multimodal omics approaches), and the computational strategies needed to integrate information across these molecular layers. We demonstrate their impact on fundamental cell biology and translational research, discuss current challenges and provide an outlook to the future.

The effect of sperm DNA fragmentation on the incidence and origin of whole and segmental chromosomal aneuploidies in human embryos

In brief

Whether sperm DNA fragmentation (SDF) affects embryo development and clinical outcomes is still controversial, which limits the utility of SDF testing in assisted reproductive technology management. This study demonstrates that high SDF is associated with the incidence of segmental chromosomal aneuploidy and increased paternal whole chromosomal aneuploidies.

Abstract

We aimed to investigate the correlation of sperm DNA fragmentation (SDF) with the incidence and paternal origin of whole and segmental chromosomal aneuploidies of embryos at the blastocyst stage. A retrospective cohort study was conducted with a total of 174 couples (women aged 35 years or younger) who underwent 238 cycles (including 748 blastocysts) of preimplantation genetic testing for monogenic diseases (PGT-M). All subjects were divided into two groups based on the sperm DNA fragmentation index (DFI) level: low DFI (<27%) and high DFI (≥27%). The rates of euploidy, whole chromosomal aneuploidy, segmental chromosomal aneuploidy, mosaicism, parental origin of aneuploidy, fertilization, cleavage, and blastocyst formation were compared between low- and high-DFI groups. We found no significant differences in fertilization, cleavage, or blastocyst formation between the two groups. Compared to that in the low-DFI group, segmental chromosomal aneuploidy rate was significantly higher in the high-DFI group (11.57% vs 5.83%, P = 0.021; OR: 2.32, 95% CI: 1.10-4.89, P = 0.028). The whole chromosomal embryonic aneuploidy of paternal origin was significantly higher in cycles with high DFI than in cycles with low DFI (46.43% vs 23.33%, P = 0.018; OR: 4.32, 95% CI: 1.06-17.66, P = 0.041). However, the segmental chromosomal aneuploidy of paternal origin was not significantly different between the two groups (71.43% vs 78.05%, P = 0.615; OR: 1.01, 95% CI: 0.16-6.40, P = 0.995). In conclusion, our results suggested that high SDF was associated with the incidence of segmental chromosomal aneuploidy and increased paternal whole chromosomal aneuploidies in embryos.

The Novel Role of Zfp296 in Mammalian Embryonic Genome Activation as an H3K9me3 Modulator

The changes in epigenetic modifications during early embryonic development significantly impact mammalian embryonic genome activation (EGA) and are species-conserved to some degree. Here, we reanalyzed the published RNA-Seq of human, mouse, and goat early embryos and found that Zfp296 (zinc finger protein 296) expression was higher at the EGA stage than at the oocyte stage in all three species (adjusted p-value < 0.05 |log2(foldchange)| ≥ 1). Subsequently, we found that Zfp296 was conserved across human, mouse, goat, sheep, pig, and bovine embryos. In addition, we identified that ZFP296 interacts with the epigenetic regulators KDM5B, SMARCA4, DNMT1, DNMT3B, HP1β, and UHRF1. The Cys₂-His₂(C2H2) zinc finger domain TYPE2 TYPE3 domains of ZFP296 co-regulated the modification level of the trimethylation of lysine 9 on the histone H3 protein subunit (H3K9me3). According to ChIP-seq analysis, ZFP296 was also enriched in Trim28, Suv39h1, Setdb1, Kdm4a, and Ehmt2 in the mESC genome. Then, knockdown of the expression of Zfp296 at the late zygote of the mouse led to the early developmental arrest of the mouse embryos and failure resulting from a decrease in H3K9me3. Together, our results reveal that Zfp296 is an H3K9me3 modulator which is essential to the embryonic genome activation of mouse embryos.

Spatial Omics Sequencing Based on Microfluidic Array Chips

Spatial profiling technologies fill the gap left by the loss of spatial information in traditional single-cell sequencing, showing great application prospects. After just a few years of quick development, spatial profiling technologies have made great progress in resolution and simplicity. This review introduces the development of spatial omics sequencing based on microfluidic array chips and describes barcoding strategies using various microfluidic designs with simplicity and efficiency. At the same time, the pros and cons of each strategy are compared. Moreover, commercialized solutions for spatial profiling are also introduced. In the end, the future perspective of spatial omics sequencing and research directions are discussed.

scTIE: data integration and inference of gene regulation using single-cell temporal multimodal data

Single-cell technologies offer unprecedented opportunities to dissect gene regulatory mechanisms in context-specific ways. Although there are computational methods for extracting gene regulatory relationships from scRNA-seq and scATAC-seq data, the data integration problem, essential for accurate cell type identification, has been mostly treated as a standalone challenge. Here we present scTIE, a unified method that integrates temporal multimodal data and infers regulatory relationships predictive of cellular state changes. scTIE uses an autoencoder to embed cells from all time points into a common space using iterative optimal transport, followed by extracting interpretable information to predict cell trajectories. Using a variety of synthetic and real temporal multimodal datasets, we demonstrate scTIE achieves effective data integration while preserving more biological signals than existing methods, particularly in the presence of batch effects and noise. Furthermore, on the exemplar multiome dataset we generated from differentiating mouse embryonic stem cells over time, we demonstrate scTIE captures regulatory elements highly predictive of cell transition probabilities, providing new potentials to understand the regulatory landscape driving developmental processes.

Comparative developmental genomics of sex-biased gene expression in early embryogenesis across mammals

BACKGROUND

Mammalian gonadal sex is determined by the presence or absence of a Y chromosome and the subsequent production of sex hormones contributes to secondary sexual differentiation. However, sex chromosome-linked genes encoding dosage-sensitive transcription and epigenetic factors are expressed well before gonad formation and have the potential to establish sex-biased expression that persists beyond the appearance of gonadal hormones. Here, we apply a comparative bioinformatics analysis on a pair of published single-cell datasets from mouse and human during very early embryogenesis-from two-cell to pre-implantation stages-to characterize sex-specific signals and to assess the degree of conservation among early acting sex-specific genes and pathways.

RESULTS

Clustering and regression analyses of gene expression across samples reveal that sex initially plays a significant role in overall gene expression patterns at the earliest stages of embryogenesis which potentially may be the byproduct of signals from male and female gametes during fertilization. Although these transcriptional sex effects rapidly diminish, sex-biased genes appear to form sex-specific protein-protein interaction networks across pre-implantation stages in both mammals providing evidence that sex-biased expression of epigenetic enzymes may establish sex-specific patterns that persist beyond pre-implantation. Non-negative matrix factorization (NMF) on male and female transcriptomes generated clusters of genes with similar expression patterns across sex and developmental stages, including post-fertilization, epigenetic, and pre-implantation ontologies conserved between mouse and human. While the fraction of sex-differentially expressed genes (sexDEGs) in early embryonic stages is similar and functional ontologies are conserved, the genes involved are generally different in mouse and human.

CONCLUSIONS

This comparative study uncovers much earlier than expected sex-specific signals in mouse and human embryos that pre-date hormonal signaling from the gonads. These early signals are diverged with respect to orthologs yet conserved in terms of function with important implications in the use of genetic models for sex-specific disease.

Technologies and applications of single-cell DNA methylation sequencing

DNA methylation is the most stable epigenetic modification. In mammals, it usually occurs at the cytosine of CpG dinucleotides. DNA methylation is essential for many physiological and pathological processes. Aberrant DNA methylation has been observed in human diseases, particularly cancer. Notably, conventional DNA methylation profiling technologies require a large amount of DNA, often from a heterogeneous cell population, and provide an average methylation level of many cells. It is often not realistic to collect sufficient numbers of cells, such as rare cells and circulating tumor cells in peripheral blood, for bulk sequencing assays. It is therefore essential to develop sequencing technologies that can accurately profile DNA methylation using small numbers of cells or even single cells. Excitingly, many single-cell DNA methylation sequencing and single-cell omics sequencing technologies have been developed, and applications of these methods have greatly expanded our understanding of the molecular mechanism of DNA methylation. Here, we summaries single-cell DNA methylation and multi-omics sequencing methods, delineate their applications in biomedical sciences, discuss technical challenges, and present our perspective on future research directions.

Characterizing Cellular Differentiation Potency and Waddington Landscape via Energy Indicator

The precise characterization of cellular differentiation potency remains an open question, which is fundamentally important for deciphering the dynamics mechanism related to cell fate transition. We quantitatively evaluated the differentiation potency of different stem cells based on the Hopfield neural network (HNN). The results emphasized that cellular differentiation potency can be approximated by Hopfield energy values. We then profiled the Waddington energy landscape of embryogenesis and cell reprogramming processes. The energy landscape at single-cell resolution further confirmed that cell fate decision is progressively specified in a continuous process. Moreover, the transition of cells from one steady state to another in embryogenesis and cell reprogramming processes was dynamically simulated on the energy ladder. These two processes can be metaphorized as the motion of descending and ascending ladders, respectively. We further deciphered the dynamics of the gene regulatory network (GRN) for driving cell fate transition. Our study proposes a new energy indicator to quantitatively characterize cellular differentiation potency without prior knowledge, facilitating the further exploration of the potential mechanism of cellular plasticity.

Single-Cell Molecular Barcoding to Decode Multimodal Information Defining Cell States

Single-cell research has provided a breakthrough in biology to understand heterogeneous cell groups, such as tissues and organs, in development and disease. Molecular barcoding and subsequent sequencing technology insert a singlecell barcode into isolated single cells, allowing separation cell by cell. Given that multimodal information from a cell defines precise cellular states, recent technical advances in methods focus on simultaneously extracting multimodal data recorded in different biological materials (DNA, RNA, protein, etc.). This review summarizes recently developed singlecell multiomics approaches regarding genome, epigenome, and protein profiles with the transcriptome. In particular, we focus on how to anchor or tag molecules from a cell, improve throughputs with sample multiplexing, and record lineages, and we further discuss the future developments of the technology.

Epigenetic Regulations in Mammalian Cells: Roles and Profiling Techniques

The genome is almost identical in all the cells of the body. However, the functions and morphologies of each cell are different, and the factors that determine them are the genes and proteins expressed in the cells. Over the past decades, studies on epigenetic information, such as DNA methylation, histone modifications, chromatin accessibility, and chromatin conformation have shown that these properties play a fundamental role in gene regulation. Furthermore, various diseases such as cancer have been found to be associated with epigenetic mechanisms. In this study, we summarized the biological properties of epigenetics and single-cell epigenomic profiling techniques, and discussed future challenges in the field of epigenetics.

Simultaneous Measurement of DNA Methylation and Nucleosome Occupancy in Single Cells Using scNOMe-Seq

Single-cell Nucleosome Occupancy and Methylome sequencing (scNOMe-seq) is a multimodal assay that simultaneously measures endogenous DNA methylation and nucleosome occupancy (i.e., chromatin accessibility) in single cells. scNOMe-seq combines the activity of a GpC Methyltransferase, an enzyme which methylates cytosines in GpC dinucleotides, with bisulfite conversion, whereby unmethylated cytosines are converted into thymines. Because GpC Methyltransferase acts only on cytosines present in non-nucleosomal regions of the genome, the subsequent bisulfite conversion step not only detects the endogenous DNA methylation, but also reveals the genome-wide pattern of chromatin accessibility. Implementing this technology at the single-cell level helps to capture the dynamics governing methylation and accessibility vary across individual cells and cell types. Here, we provide a scalable plate-based protocol for preparing scNOMe-seq libraries from single nucleus suspensions.

Simultaneous Single-Cell Profiling of the Transcriptome and Accessible Chromatin Using SHARE-seq

The ability to analyze the transcriptomic and epigenomic states of individual single cells has in recent years transformed our ability to measure and understand biological processes. Recent advancements have focused on increasing sensitivity and throughput to provide richer and deeper biological insights at the cellular level. The next frontier is the development of multiomic methods capable of analyzing multiple features from the same cell, such as the simultaneous measurement of the transcriptome and the chromatin accessibility of candidate regulatory elements. In this chapter, we discuss and describe SHARE-seq (Simultaneous high-throughput ATAC, and RNA expression with sequencing) for carrying out simultaneous chromatin accessibility and transcriptome measurements in single cells, together with the experimental and analytical considerations for achieving optimal results.

Single-cell multi-omics integration for unpaired data by a siamese network with graph-based contrastive loss

BACKGROUND

Single-cell omics technology is rapidly developing to measure the epigenome, genome, and transcriptome across a range of cell types. However, it is still challenging to integrate omics data from different modalities. Here, we propose a variation of the Siamese neural network framework called MinNet, which is trained to integrate multi-omics data on the single-cell resolution by using graph-based contrastive loss.

RESULTS

By training the model and testing it on several benchmark datasets, we showed its accuracy and generalizability in integrating scRNA-seq with scATAC-seq, and scRNA-seq with epitope data. Further evaluation demonstrated our model's unique ability to remove the batch effect, a common problem in actual practice. To show how the integration impacts downstream analysis, we established model-based smoothing and cis-regulatory element-inferring method and validated it with external pcHi-C evidence. Finally, we applied the framework to a COVID-19 dataset to bolster the original work with integration-based analysis, showing its necessity in single-cell multi-omics research.

CONCLUSIONS

MinNet is a novel deep-learning framework for single-cell multi-omics sequencing data integration. It ranked top among other methods in benchmarking and is especially suitable for integrating datasets with batch and biological variances. With the single-cell resolution integration results, analysis of the interplay between genome and transcriptome can be done to help researchers understand their data and question.

Current status of genome-wide epigenetic profiling of mammalian preimplantation embryos

Background

Genome-wide information on epigenetic modifications in mammalian preimplantation embryos was an unexplored sanctuary of valuable research insights protected by the difficulty of its analysis. However, that is no longer the case, and many epigenome maps are now available for sightseeing there.

Methods

This review overviews the current status of genome-wide epigenetic profiling in terms of DNA methylome and histone modifications in mammalian preimplantation embryos.

Main findings

As the sensitivity of methods for analyzing epigenetic modifications increased, pioneering work began to explore the genome-wide epigenetic landscape in the mid-2010s, first for DNA methylation and then for histone modifications. Since then, a huge amount of data has accumulated, revealing typical epigenetic profiles in preimplantation development and, more recently, changes in response to environmental interventions.

Conclusions

These accumulating data may be used to improve the quality of preimplantation embryos, both in terms of their short-term developmental competence and their subsequent long-term health implications.

Cloning by SCNT: Integrating Technical and Biology-Driven Advances

Somatic cell nuclear transfer (SCNT) into enucleated oocytes initiates nuclear reprogramming of lineage-committed cells to totipotency. Pioneer SCNT work culminated with cloned amphibians from tadpoles, while technical and biology-driven advances led to cloned mammals from adult animals. Cloning technology has been addressing fundamental questions in biology, propagating desired genomes, and contributing to the generation of transgenic animals or patient-specific stem cells. Nonetheless, SCNT remains technically complex and cloning efficiency relatively low. Genome-wide technologies revealed barriers to nuclear reprogramming, such as persistent epigenetic marks of somatic origin and reprogramming resistant regions of the genome. To decipher the rare reprogramming events that are compatible with full-term cloned development, it will likely require technical advances for large-scale production of SCNT embryos alongside extensive profiling by single-cell multi-omics. Altogether, cloning by SCNT remains a versatile technology, while further advances should continuously refresh the excitement of its applications.

Characterizing cis-regulatory elements using single-cell epigenomics

Cell type-specific gene expression patterns and dynamics during development or in disease are controlled by cis-regulatory elements (CREs), such as promoters and enhancers. Distinct classes of CREs can be characterized by their epigenomic features, including DNA methylation, chromatin accessibility, combinations of histone modifications and conformation of local chromatin. Tremendous progress has been made in cataloguing CREs in the human genome using bulk transcriptomic and epigenomic methods. However, single-cell epigenomic and multi-omic technologies have the potential to provide deeper insight into cell type-specific gene regulatory programmes as well as into how they change during development, in response to environmental cues and through disease pathogenesis. Here, we highlight recent advances in single-cell epigenomic methods and analytical tools and discuss their readiness for human tissue profiling.

Zygotic genome activation by the totipotency pioneer factor Nr5a2

Life begins with a switch in genetic control from the maternal to the embryonic genome during zygotic genome activation (ZGA). Despite its importance, the essential regulators of ZGA remain largely unknown in mammals. On the basis of de novo motif searches, we identified the orphan nuclear receptor Nr5a2 as a key activator of major ZGA in mouse two-cell embryos. Nr5a2 is required for progression beyond the two-cell stage. It binds to its motif within SINE B1/Alu retrotransposable elements found in cis-regulatory regions of ZGA genes. Chemical inhibition suggests that 72% of ZGA genes are regulated by Nr5a2 and potentially other orphan nuclear receptors. Nr5a2 promotes chromatin accessibility during ZGA and binds nucleosomal DNA in vitro. We conclude that Nr5a2 is an essential pioneer factor that regulates ZGA.

Leukocyte telomere length in children born following blastocyst-stage embryo transfer

Perinatal and childhood adverse outcomes associated with assisted reproductive technology (ART) has been reported, but it remains unknown whether the initial leukocyte telomere length (LTL), which is an indicator of age-related phenotypes in later life, is affected. Here, we estimated the LTLs of 1,137 individuals from 365 families, including 202 children conceived by ART and 205 children conceived spontaneously from two centers of the China National Birth Cohort, using whole-genome sequencing (WGS) data. One-year-old children conceived by ART had shorter LTLs than those conceived spontaneously (beta, -0.36; P = 1.29 × 10-3) after adjusting for plurality, sex and other potential confounding factors. In particular, blastocyst-stage embryo transfer was associated with shorter LTL (beta, -0.54, P = 2.69 × 10-3) in children conceived by ART. The association was validated in 586 children conceived by ART from five centers using different LTL quantification methods (that is, WGS or qPCR). Blastocyst-stage embryo transfer resulted in shorter telomere lengths in mice at postnatal day 1 (P = 2.10 × 10-4) and mice at 6 months (P = 0.042). In vitro culturing of mice embryos did not result in shorter telomere lengths in the late cleavage stage, but it did suppress telomerase activity in the early blastocyst stage. Our findings demonstrate the need to evaluate the long-term consequences of ART, particularly for aging-related phenotypes, in children conceived by ART.

Single-cell technologies: From research to application

In recent years, more and more single-cell technologies have been developed. A vast amount of single-cell omics data has been generated by large projects, such as the Human Cell Atlas, the Mouse Cell Atlas, the Mouse RNA Atlas, the Mouse ATAC Atlas, and the Plant Cell Atlas. Based on these single-cell big data, thousands of bioinformatics algorithms for quality control, clustering, cell-type annotation, developmental inference, cell-cell transition, cell-cell interaction, and spatial analysis are developed. With powerful experimental single-cell technology and state-of-the-art big data analysis methods based on artificial intelligence, the molecular landscape at the single-cell level can be revealed. With spatial transcriptomics and single-cell multi-omics, even the spatial dynamic multi-level regulatory mechanisms can be deciphered. Such single-cell technologies have many successful applications in oncology, assisted reproduction, embryonic development, and plant breeding. We not only review the experimental and bioinformatics methods for single-cell research, but also discuss their applications in various fields and forecast the future directions for single-cell technologies. We believe that spatial transcriptomics and single-cell multi-omics will become the next booming business for mechanism research and commercial industry.

Extracellular cell-free RNA profile in human large follicles and small follicles

Background: Previous studies have shown that a large number of valuable and functional cell-free RNAs (cfRNAs) were found in follicular fluid. However, the species and characteristics of follicular fluid cfRNAs have not been reported. Furthermore, their implications are still barely understood in the evaluation of follicular fluid from follicles of different sizes, which warrants further studies.

Objective: This study investigated the landscape and characteristics of follicular fluid cfRNAs, the source of organization, and the potential for distinguishing between follicles of different sizes.

Methods: Twenty-four follicular fluid samples were collected from 20 patients who received in vitro fertilization (n = 9) or ICSI (n = 11), including 16 large follicular fluid and 8 small follicular fluid samples. Also, the cfRNA profile of follicular fluid samples was analyzed by RNA sequencing.

Results: This result indicated that the concentration of follicular fluid cfRNAs ranged from 0.78 to 8.76 ng/ml, and fragment length was 20–200 nucleotides. The concentration and fragment length of large follicular fluid and small follicular fluid samples were not significantly different (p &gt; 0.05). The technical replica correlation of follicular fluid samples ranged from 0.3 to 0.9, and the correlation of small follicular fluid samples was remarkably (p &lt; 0.001) lower than that of large follicular fluid samples. Moreover, this study found that cfRNAs of the follicular fluid could be divided into 37 Ensembl RNA biotypes, and a large number of mRNAs, circRNAs, and lncRNAs were observed in the follicular fluid. The number of cfRNAs in large follicular fluid was remarkably (p &lt; 0.05) higher than that of small follicular fluid. Furthermore, the follicular fluid contained a large amount of intact mRNA and splice junctions and a large number of tissue-derived RNAs, which are at a balanced state of supply and elimination in the follicular fluid. KEGG pathway analysis showed that differentially expressed cfRNAs were enriched in several pathways, including thyroid hormone synthesis, the cGMP-PKG signaling pathway, and inflammatory mediator regulation of TRP channels. In addition, we further showed that four cfRNAs (TK2, AHDC1, PHF21A, and TTYH1) serve as a potential indicator to distinguish the follicles of different sizes. The ROC curve shows great potential to predict follicular fluid from follicles of different sizes [area under the curve (AUC) &gt; 0.88].

Conclusion: Overall, our study revealed that a large number of cfRNAs could be detected in follicular fluid and could serve as a potential non-invasive biomarker in distinguishing between follicles of different sizes. These results may inform the study of the utility and implementation of cfRNAs in clinical practice.

The role of single-cell genomics in human genetics

Single-cell sequencing is a powerful approach that can detect genetic alterations and their phenotypic consequences in the context of human development, with cellular resolution. Humans start out as single-cell zygotes and undergo fission and differentiation to develop into multicellular organisms. Before fertilisation and during development, the cellular genome acquires hundreds of mutations that propagate down the cell lineage. Whether germline or somatic in nature, some of these mutations may have significant genotypic impact and lead to diseased cellular phenotypes, either systemically or confined to a tissue. Single-cell sequencing enables the detection and monitoring of the genotype and the consequent molecular phenotypes at a cellular resolution. It offers powerful tools to compare the cellular lineage between 'normal' and 'diseased' conditions and to establish genotype-phenotype relationships. By preserving cellular heterogeneity, single-cell sequencing, unlike bulk-sequencing, allows the detection of even small, diseased subpopulations of cells within an otherwise normal tissue. Indeed, the characterisation of biopsies with cellular resolution can provide a mechanistic view of the disease. While single-cell approaches are currently used mainly in basic research, it can be expected that applications of these technologies in the clinic may aid the detection, diagnosis and eventually the treatment of rare genetic diseases as well as cancer. This review article provides an overview of the single-cell sequencing technologies in the context of human genetics, with an aim to empower clinicians to understand and interpret the single-cell sequencing data and analyses. We discuss the state-of-the-art experimental and analytical workflows and highlight current challenges/limitations. Notably, we focus on two prospective applications of the technology in human genetics, namely the annotation of the non-coding genome using single-cell functional genomics and the use of single-cell sequencing data for in silico variant prioritisation.

Single-cell multiomics sequencing reveals the reprogramming defects in embryos generated by round spermatid injection

Round spermatid injection (ROSI) technique holds great promise for clinical treatment of a proportion of infertile men. However, the compromised developmental potential of ROSI embryos largely limits the clinical application, and the mechanisms are not fully understood. Here, we describe the transcriptome, chromatin accessibility, and DNA methylation landscapes of mouse ROSI embryos derived from early-stage round spermatids using a single-cell multiomics sequencing approach. By interrogating these data, we identify the reprogramming defects in ROSI embryos at the pronuclear stages, which are mainly associated with the misexpression of a cohort of minor zygotic genome activation genes. We screen a small compound, A366, that can significantly increase the developmental potential of ROSI embryos, in which A366 can partially overcome the reprogramming defects by amending the epigenetic and transcriptomic states. Collectively, our study uncovers the reprogramming defects in ROSI embryos for understanding the mechanisms underlying compromised developmental potential and offers an avenue for ROSI technique optimization.

2,4,6-triiodophenol exhibits embryotoxicity to pre-implantation mouse embryos in an in vitro exposure model

2,4,6-triiodophenol (TIP), a novel type of halophenolic disinfection byproducts, has been widely detected in water bodies, even in drinking water. Recently, TIP has drawn increasing concerns on account of considerable developmental toxicity towards lower organisms and cytotoxicity for mammalian cells. However, it remains unknown about its toxicity on mammalian pre-implantation embryos. Here, by exposing mouse zygotes derived in vitro fertilization to TIP, which ranged from 5 to 50 μM, we found that TIP impaired the quality of pre-implantation mouse embryos in a dose-dependent manner, inducing decline of both total and trophectoderm cell numbers, enhancing caspase 3/7 activity and reactive oxygen species generation, though it did not decrease blastocyst formation efficiency. For the sake that only high qualified embryos are able to implant in endometrium and generate health body finally, we applied a previously modified in vitro culture system to assess TIP-exposed blastocysts' further developmental potency beyond pre-implantation stage. Surprisingly, although the exposed dose was only 5 μM and TIP was removed as soon as the zygotes reached blastocyst stage, these blastocysts still nearly lost their implantation and egg cylinder formation ability, exhibiting abnormal embryonic lineage differentiation pattern as well. Therefore, our study not only entirely shows TIP embryonic toxicity on mouse pre-implantation embryos, but also proposes a model to evaluate embryotoxicity from the zygote to egg cylinder stage.

ELF4 is critical to zygotic gene activation and epigenetic reprogramming during early embryonic development in pigs

Zygotic gene activation (ZGA) and epigenetic reprogramming are critical in early embryonic development in mammals, and transcription factors are involved in regulating these events. However, the effects of ELF4 on porcine embryonic development remain unclear. In this study, the expression of ELF4 was detected in early porcine embryos and different tissues. By knocking down ELF4, the changes of H3K9me3 modification, DNA methylation and ZGA-related genes were analyzed. Our results showed that ELF4 was expressed at all stages of early porcine embryos fertilized in vitro (IVF), with the highest expression level at the 8-cell stage. The embryonic developmental competency and blastocyst quality decreased after ELF4 knockdown (20.70% control vs. 17.49% si-scramble vs. 2.40% si-ELF4; p < 0.001). Knockdown of ELF4 induced DNA damage at the 4-cell stage. Interfering with ELF4 resulted in abnormal increases in H3K9me3 and DNA methylation levels at the 4-cell stage and inhibited the expression of genes related to ZGA. These results suggest that ELF4 affects ZGA and embryonic development competency in porcine embryos by maintaining genome integrity and regulating dynamic changes of H3K9me3 and DNA methylation, and correctly activating ZGA-related genes to promote epigenetic reprogramming. These results provide a theoretical basis for further studies on the regulatory mechanisms of ELF4 in porcine embryos.

Single cell cancer epigenetics

Bulk sequencing methodologies have allowed us to make great progress in cancer research. Unfortunately, these techniques lack the resolution to fully unravel the epigenetic mechanisms that govern tumor heterogeneity. Consequently, many novel single cell-sequencing methodologies have been developed over the past decade, allowing us to explore the epigenetic components that regulate different aspects of cancer heterogeneity, namely: clonal heterogeneity, tumor microenvironment (TME), spatial organization, intratumoral differentiation programs, metastasis, and resistance mechanisms. In this review, we explore the different sequencing techniques that enable researchers to study different aspects of epigenetics (DNA methylation, chromatin accessibility, histone modifications, DNA-protein interactions, and chromatin 3D architecture) at the single cell level, their potential applications in cancer, and their current technical limitations.

Advances in studying human gametogenesis and embryonic development in China

Reproductive medicine in China has developed rapidly since 1988 due to the support from the government and scientific exploration. However, the success rate of assisted reproduction technology (ART) is around 30-40% and many unknown "black boxes" in gametogenesis and embryo development are still present. With the development of single-cell and low-input sequencing technologies, the network of transcriptome and epigenetic regulation (DNA methylation, chromatin accessibility, and histone modifications) during the development of human primordial germ cells (PGCs), gametes and embryos has been investigated in depth. Furthermore, pre-implantation genetic testing (PGT) has also rapidly developed. In this review, we summarize and analyze China's outstanding progress in these fields.

Single-cell multi-omics sequencing and its applications in studying the nervous system

Single-cell sequencing has become one of the most powerful and popular techniques in dissecting molecular heterogeneity and modeling the cellular architecture of a biological system. During the past twenty years, the throughput of single-cell sequencing has increased from hundreds of cells to over tens of thousands of cells in parallel. Moreover, this technology has been developed from sequencing transcriptome to measure different omics such as DNA methylome, chromatin accessibility, and so on. Currently, multi-omics which can analyze different omics in the same cell is rapidly advancing. This work advances the study of many biosystems, including the nervous system. Here, we review current single-cell multi-omics sequencing techniques and describe how they improve our understanding of the nervous system. Finally, we discuss the open scientific questions in neural research that may be answered through further improvement of single-cell multi-omics sequencing technology.

Maternal DDB1 regulates apoptosis and lineage differentiation in porcine preimplantation embryos

CONTEXT

Maternal-effect genes (MEGs) play a critical role in modulating both cellular and molecular biology events in preimplantation embryonic development. Damage-specific DNA binding protein 1 (DDB1) is a gene that participates in meiotic resumption, ovulation, and embryonic stem cell maintenance. Its function in preimplantation development is not well-studied.

AIMS

We aimed to explore the expression pattern, genomic heritage, and potential molecular mechanisms of DDB1 in preimplantation embryos in porcine.

METHODS

In this study, RNA interference, microinjection, RT-qPCR, immunofluorescence staining and single-cell RNA sequencing were used to explore the molecular function of DDB1 in porcine preimplantation embryos.

KEY RESULTS

DDB1 was found to be expressed in germinal vesicle (GV) and Meiosis II (MII) oocytes and in preimplantation embryos. We confirmed it is a MEG. DDB1-deficient blastocysts had a significantly reduced number of trophectoderm cells, an increased apoptotic cell number and increased apoptosis index. According to a next-generation sequencing (NGS) analysis, 236 genes (131 upregulated and 105 downregulated) significantly changed in the DDB1-deficient morula. The myeloid leukaemia factor 1 (MLF1) and yes-associated protein 1 (YAP1) expressions were significantly upregulated and downregulated respectively, in the DDB1-deficient morula. In combination with the decreased expression of TEAD4, CDX2, GATA3, OCT4, and NANOG and the increased expression of SOX2 in the blastocyst, DDB1 may play a role in determining lineage differentiation and pluripotency maintenance.

CONCLUSIONS

DDB1 is a MEG and it plays a crucial role in porcine preimplantation embryonic development.

IMPLICATIONS

This study provides a theoretical basis for further understanding the molecular mechanisms of preimplantation embryo development.

Decoding Lung Cancer at Single-Cell Level

Lung cancer is the leading cause of cancer death due to its high degree of malignancy, rapid growth, and early metastasis. Recent studies have found that lung cancer has a high degree of heterogeneity which is characterized by the mixture of different tumor cell types. However, the driving genetic/epigenetic mechanism of lung cancer heterogeneity, how different types of cells interact, and the relationship between heterogeneity and drug resistance have been poorly understood. Single-cell technology can decompose high throughput sequencing information into each cell and provide single-cell information in high resolution. By using single-cell analysis, researchers can not only fully understand the molecular characteristics of different cell types in the same tissue, but also define completely new cell types. Thus, single-cell analysis has been widely utilized in systems biology, drug discovery, disease diagnosis and precision medicine. We review recent exploration of the mechanism of heterogeneity, tumor microenvironment and drug resistance in lung cancer by using single-cell analysis. We propose that the recent findings may pave new ways for the treatment strategies of lung cancer.

Breaking the Immune Complexity of the Tumor Microenvironment Using Single-Cell Technologies

Tumors are not a simple aggregate of transformed cells but rather a complicated ecosystem containing various components, including infiltrating immune cells, tumor-related stromal cells, endothelial cells, soluble factors, and extracellular matrix proteins. Profiling the immune contexture of this intricate framework is now mandatory to develop more effective cancer therapies and precise immunotherapeutic approaches by identifying exact targets or predictive biomarkers, respectively. Conventional technologies are limited in reaching this goal because they lack high resolution. Recent developments in single-cell technologies, such as single-cell RNA transcriptomics, mass cytometry, and multiparameter immunofluorescence, have revolutionized the cancer immunology field, capturing the heterogeneity of tumor-infiltrating immune cells and the dynamic complexity of tenets that regulate cell networks in the tumor microenvironment. In this review, we describe some of the current single-cell technologies and computational techniques applied for immune-profiling the cancer landscape and discuss future directions of how integrating multi-omics data can guide a new "precision oncology" advancement.

Multi-omics single-cell data integration and regulatory inference with graph-linked embedding

Despite the emergence of experimental methods for simultaneous measurement of multiple omics modalities in single cells, most single-cell datasets include only one modality. A major obstacle in integrating omics data from multiple modalities is that different omics layers typically have distinct feature spaces. Here, we propose a computational framework called GLUE (graph-linked unified embedding), which bridges the gap by modeling regulatory interactions across omics layers explicitly. Systematic benchmarking demonstrated that GLUE is more accurate, robust and scalable than state-of-the-art tools for heterogeneous single-cell multi-omics data. We applied GLUE to various challenging tasks, including triple-omics integration, integrative regulatory inference and multi-omics human cell atlas construction over millions of cells, where GLUE was able to correct previous annotations. GLUE features a modular design that can be flexibly extended and enhanced for new analysis tasks. The full package is available online at https://github.com/gao-lab/GLUE.

Different single-cell data modalities are integrated at atlas-scale by modeling regulatory interactions.

Rolling back human pluripotent stem cells to an eight-cell embryo-like stage

After fertilization, the quiescent zygote experiences a burst of genome activation that initiates a short-lived totipotent state. Understanding the process of totipotency in human cells would have broad applications. However, in contrast to in mice1,2, demonstration of the time of zygotic genome activation or the eight-cell (8C) stage in in vitro cultured human cells has not yet been reported, and the study of embryos is limited by ethical and practical considerations. Here we describe a transgene-free, rapid and controllable method for producing 8C-like cells (8CLCs) from human pluripotent stem cells. Single-cell analysis identified key molecular events and gene networks associated with this conversion. Loss-of-function experiments identified fundamental roles for DPPA3, a master regulator of DNA methylation in oocytes3, and TPRX1, a eutherian totipotent cell homeobox (ETCHbox) family transcription factor that is absent in mice4. DPPA3 induces DNA demethylation throughout the 8CLC conversion process, whereas TPRX1 is a key executor of 8CLC gene networks. We further demonstrate that 8CLCs can produce embryonic and extraembryonic lineages in vitro or in vivo in the form of blastoids5 and complex teratomas. Our approach provides a resource to uncover the molecular process of early human embryogenesis.

Update on the Epigenomic Implication of Embryo Cryopreservation Methods Applied in Assisted Reproductive Technologies With Potential Long-Term Health Effects

Cryopreservation of embryos has become an efficient method in Assisted Reproductive Technologies (ART) and these methods are currently performed at nearly all fertility centers around the globe. Cryopreservation of supernumerary embryos has contributed to an increase in cumulative pregnancy rates and as a consequence, an increasing number of children are being born through these techniques worldwide. However, long-term follow-up studies of children born through ART are scarce, and concerns about the long-term health effects on individuals conceived through ART have been raised. The relevant genomic transformations that occur at the time cryopreservation is usually applied to embryos may have potential epigenetic risks. With advances in multi-omic single cell technologies, new ways to assess the (epi)genomic status during early embryo development have now become feasible. These novel strategies could provide a revolutionary opportunity to understand the actual impact of ART, but also may help future developments aiming at increase both their efficiency and safety. Here we outline insights in current knowledge and research on the impact of cryopreservation on embryos, the possible consequences at epigenetic level and how emerging new high-throughput technologies can be used for their assessment.

Single-Cell Multiomics Techniques: From Conception to Applications

Recent advances in methods for single-cell analyses and barcoding strategies have led to considerable progress in research. The development of multiplexed assays offers the possibility to conduct parallel analyses of multiple factors and processes for comprehensive characterization of cellular and molecular states in health and disease. These technologies have expanded extremely rapidly in the past years and constantly evolve and provide better specificity, precision and resolution. This review summarizes recent progress in single-cell multiomics approaches, and focuses, in particular, on the most innovative techniques that integrate genome, epigenome and transcriptome profiling. It describes the methodologies, discusses their advantages and limitations, and explains how they have been applied to studies on cell heterogeneity and differentiation, and epigenetic reprogramming.

Exploring the Developmental Potential of Human Germinal Vesicle Oocytes Aiming at Fertility Preservation: Can We Increase the Yields of Competent Oocytes through IVM Combined with Vitrification?

The rescue in vitro maturation (rIVM) of germinal vesicle oocytes (GVs) has been proposed to improve the total number of mature oocytes in women undergoing fertility preservation. Currently, there is no consensus about the clinical utility of this practice, and heterogeneity in the protocols used may influence the final outcomes. This study investigated the developmental potential of mature metaphase II (MII) human oocytes obtained from GVs after rIVM and the impact of applying vitrification at different timepoints either before or after rIVM. After randomization, oocytes were assigned to undergo rIVM and thereafter vitrification or intracytoplasmic sperm injection (ICSI), or to undergo direct vitrification-warming and thereafter rIVM and ICSI. The likelihood of obtaining MII oocytes was just slightly higher in the fresh rIVM group compared to the vitrification-warming-rIVM group. When comparing fresh rIVM that underwent subsequently ICSI, the fertilization and developmental rates up to the blastocyst stage were seen to be reduced in both groups that underwent vitrification either before or after rIVM. Although some blastocysts were obtained in the fresh rIVM-ICSI group, the efficacy of these methods was low overall, suggesting that the further development of protocols for IVM conducted early after denudation is needed to improve the final results of rIVM aiming at fertility preservation.

Epigenetic reorganization during early embryonic lineage specification

BACKGROUND

Dynamic chromatin reorganization occurs during two waves of cell lineage specification process, blastocyst formation and gastrulation, to generate distinct cell types. Epigenetic defects have been associated with severe developmental defects and diseases. How epigenetic remodeling coordinates the two lineage specification waves is becoming uncovered, benefiting from the development and application of new technologies including low-input or single-cell epigenome analysis approached in the past few years.

OBJECTIVE

In this review, we aim to highlight the most recent findings on epigenetic remodeling in cell lineage specification during blastocyst formation and gastrulation.

METHODS

First, we introduce how DNA methylation dynamically changes in blastocyst formation and gastrulation and its function in transcriptional regulation lineage-specific genes. Then, we discuss widespread remodeling of histone modification at promoters and enhancers in orchestrating the trajectory of cell lineage specification. Finally, we review dynamics of chromatin accessibility and 3D structure regulating developmental gene expression and associating with specific transcription factor binding events at stage specific manner. We also highlight the key questions that remain to be answered to fully understand chromatin regulation and reorganization in lineage specification.

CONCLUSION

Here, we summarize the recent advances and discoveries on epigenetic reorganization and its roles in blastocyst formation and gastrulation, and how it cooperates with the lineage specification, painting from global sequencing data from mouse in vivo tissues.

Computational strategies for single-cell multi-omics integration

Single-cell omics technologies are currently solving biological and medical problems that earlier have remained elusive, such as discovery of new cell types, cellular differentiation trajectories and communication networks across cells and tissues. Current advances especially in single-cell multi-omics hold high potential for breakthroughs by integration of multiple different omics layers. To pair with the recent biotechnological developments, many computational approaches to process and analyze single-cell multi-omics data have been proposed. In this review, we first introduce recent developments in single-cell multi-omics in general and then focus on the available data integration strategies. The integration approaches are divided into three categories: early, intermediate, and late data integration. For each category, we describe the underlying conceptual principles and main characteristics, as well as provide examples of currently available tools and how they have been applied to analyze single-cell multi-omics data. Finally, we explore the challenges and prospective future directions of single-cell multi-omics data integration, including examples of adopting multi-view analysis approaches used in other disciplines to single-cell multi-omics.

Single cell regulatory landscape of the mouse kidney highlights cellular differentiation programs and disease targets

Determining the epigenetic program that generates unique cell types in the kidney is critical for understanding cell-type heterogeneity during tissue homeostasis and injury response. Here, we profile open chromatin and gene expression in developing and adult mouse kidneys at single cell resolution. We show critical reliance of gene expression on distal regulatory elements (enhancers). We reveal key cell type-specific transcription factors and major gene-regulatory circuits for kidney cells. Dynamic chromatin and expression changes during nephron progenitor differentiation demonstrates that podocyte commitment occurs early and is associated with sustained Foxl1 expression. Renal tubule cells follow a more complex differentiation, where Hfn4a is associated with proximal and Tfap2b with distal fate. Mapping single nucleotide variants associated with human kidney disease implicates critical cell types, developmental stages, genes, and regulatory mechanisms. The single cell multi-omics atlas reveals key chromatin remodeling events and gene expression dynamics associated with kidney development.