Single-cell RNA-Seq profiling of human preimplantation embryos and embryonic stem cells. Nat Struct Mol Biol. 2013;20:1131-1139. [PMID: 23934149 DOI: 10.1038/nsmb.2660]

Circadian rhythm disruptions exacerbate inner ear damage in a murine endolymphatic hydrops model

Meniere's disease (MD) is an inner ear disease characterized by endolymphatic hydrops (EH). Maintaining a regular daily routine is crucial for MD patients. However, the relationship between circadian rhythms and MD remains unclear. Therefore, we investigated the effect of circadian rhythm on endolymphatic hydrops and its underlying mechanisms. Mice with endolymphatic hydrops were subjected to chronic jet lag (CJL) conditions to simulate the MD patients under circadian rhythm disruptions. We assessed whether this disruption would exacerbate inner ear damage with endolymphatic hydrops. RNA-seq of the inner ear and bioinformatic analysis were performed. Then, the expression of PER2, AQP2, AQP4, AQP5, and BDNF were assessed, and the morphological changes were evaluated in the inner ear. Our findings showed circadian rhythm disruption affected the cochlear internal clock genes in the inner ear, particularly in mice with EH. EH mice under CJL conditions exhibited exacerbated hearing impairment and an increased severity of EH. GO enrichment analysis revealed that the regulation of fluid homeostasis and neurotransmitter release at synapses were significantly enriched. Disruption of circadian rhythms disturbed the expression pattern of PER2, reduced BDNF levels, and affected the expression of aquaporins in the cochlea. Moreover, the disruption of circadian rhythm compromised inner hair cell synapses and auditory nerve fibers. This study indicated that disruption of circadian rhythms may exacerbate inner ear damage in endolymphatic hydrops mice by affecting the aquaporins and compromising synapses and auditory nerves in the inner ear. BDNF and PER2 may play a central role in these pathophysiological processes.

Krüppel-like Factors Play Essential Roles in Regulating Pluripotency and the Formation of Neural Crest Stem Cells

The evolutionary transition from simple chordate body plans to complex vertebrate body plans was driven by the acquisition of the neural crest, a stem cell population that retains broad, multi-germ layer developmental potential long after most embryonic cells have become lineage restricted. We have previously shown that neural crest cells share significant gene regulatory architecture with pluripotent blastula stem cells. Here we examine the roles that Krüppel-like Family (Klf) transcription factors play in these stem cell populations. Although Klf4 has established roles in regulating pluripotency in mammalian stem cells cultures, we find that in Xenopus it is klf2 that is highly expressed in pluripotent blastula stem cells. klf2 expression is down-regulated as cells transition to a neural crest state while a related klf factor, klf17, is significantly up regulated in response to neural crest induction. We used gain and loss of function studies to compare the activities of these closely related factors and found that they have both shared and distinct activities. Inhibition of either klf2 or klf17 activity led to significantly expanded expression of pluripotency, neural plate border and neural crest factors in neurula stage embryos, leading us to hypothesize that klf factors regulate the exit from pluripotency and proper establishment of the boundary of the neural crest domain. To gain further insights into the role of klf factors in the evolution of the neural crest, we examined their expression in the jawless vertebrate, Petromyzon marinus ( sea lamprey). We find that lamprey have a klf2/4 and a klf17 gene, but that only klf17 is expressed in blastula and neural crest stem cells. Moreover, ectopic expression of lamprey klf17 in Xenopus embryos phenocopies Xenopus klf17 activity. These data suggest that klf17, rather than klf4, may have been the ancestral klf factor that functioned in these GRNs in stem vertebrates.

Unveiling Long Non-coding RNA Networks from Single-Cell Omics Data Through Artificial Intelligence

Single-cell omics technologies have revolutionized the study of long non-coding RNAs (lncRNAs), offering unprecedented resolution in elucidating their expression dynamics, cell-type specificity, and associated gene regulatory networks (GRNs). Concurrently, the integration of artificial intelligence (AI) methodologies has significantly advanced our understanding of lncRNA functions and its implications in disease pathogenesis. This chapter discusses the progress in single-cell omics data analysis, emphasizing its pivotal role in unraveling the molecular mechanisms underlying cellular heterogeneity and the associated regulatory networks involving lncRNAs. Additionally, we provide a summary of single-cell omics resources and AI models for constructing single-cell gene regulatory networks (scGRNs). Finally, we explore the challenges and prospects of exploring scGRNs in the context of lncRNA biology.

Transposable element activity captures human pluripotent cell states

Human pluripotent stem cells (hPSCs) exist in multiple, transcriptionally distinct states and serve as powerful models for studying human development. Despite their significance, the molecular determinants and pathways governing these pluripotent states remain incompletely understood. Here, we demonstrate that transposable elements act as sensitive indicators of distinct pluripotent cell states. We engineered hPSCs with fluorescent reporters to capture the temporal expression dynamics of two state-specific transposable elements, LTR5_Hs, and MER51B. This dual reporter system enables real-time monitoring and isolation of stem cells transitioning from naïve to primed pluripotency and further towards differentiation, serving as a more accurate readout of pluripotency states compared to conventional systems. Unexpectedly, we identified a rare, metastable cell population within primed hPSCs, marked by transcripts related to preimplantation embryo development and which is associated with a DNA damage response. Moreover, our system establishes the chromatin factor NSD1 and the RNA-binding protein FUS as potent molecular safeguards of primed pluripotency. Our study introduces a novel system for investigating cellular potency and provides key insights into the regulation of embryonic development.

A comprehensive human embryo reference tool using single-cell RNA-sequencing data

Stem cell-based embryo models offer unprecedented experimental tools for studying early human development. The usefulness of embryo models hinges on their molecular, cellular and structural fidelities to their in vivo counterparts. To authenticate human embryo models, single-cell RNA sequencing has been utilized for unbiased transcriptional profiling. However, an organized and integrated human single-cell RNA-sequencing dataset, serving as a universal reference for benchmarking human embryo models, remains unavailable. Here we developed such a reference through the integration of six published human datasets covering development from the zygote to the gastrula. Lineage annotations are contrasted and validated with available human and nonhuman primate datasets. Using stabilized Uniform Manifold Approximation and Projection, we constructed an early embryogenesis prediction tool, where query datasets can be projected on the reference and annotated with predicted cell identities. Using this reference tool, we examined published human embryo models, highlighting the risk of misannotation when relevant references are not utilized for benchmarking and authentication.

Deep learning-based models for preimplantation mouse and human embryos based on single-cell RNA sequencing

The rapid growth of single-cell transcriptomic technology has produced an increasing number of datasets for both embryonic development and in vitro pluripotent stem cell-derived models. This avalanche of data surrounding pluripotency and the process of lineage specification has meant it has become increasingly difficult to define specific cell types or states in vivo, and compare these with in vitro differentiation. Here we utilize a set of deep learning tools to integrate and classify multiple datasets. This allows the definition of both mouse and human embryo cell types, lineages and states, thereby maximizing the information one can garner from these precious experimental resources. Our approaches are built on recent initiatives for large-scale human organ atlases, but here we focus on material that is difficult to obtain and process, spanning early mouse and human development. Using publicly available data for these stages, we test different deep learning approaches and develop a model to classify cell types in an unbiased fashion at the same time as defining the set of genes used by the model to identify lineages, cell types and states. We used our models trained on in vivo development to classify pluripotent stem cell models for both mouse and human development, showcasing the importance of this resource as a dynamic reference for early embryogenesis.

Circular RNAs as a novel class of potential therapeutic and diagnostic biomarkers in reproductive biology/diseases

Infertility is a prevalent problem among 10% of people within their reproductive years. Sometimes, even advanced treatment options like assisted reproduction technology have the potential to result in failed implantation. Because of the expected changes in gene expression during both in vitro and in vivo fertilization processes, these methods of assisting fertility have also been associated with undesirable pregnancy outcomes related to infertility. In this aspect, Circular RNAs (circRNAs) play a crucial role as epigenetic modifiers in a wide range of biological and pathological activities, including problems with fertility. CircRNAs are integral pieces in multiple cellular functions, including moving substances within the nucleus, silencing one X chromosome, cell death, the ability of stem cells to differentiate into different cell types, and the process of gene expression inherited from parental genes. Due to the progress made in high-speed gene sequencing, a large amount of circRNA molecules have been detected, revealing their significant functions in diverse biological functions like enhancing testicular development, preserving the differentiation and renewal of spermatogonial cells, and controlling spermatocyte meiosis. Moreover, these non-coding RNAs contribute in different aspects of female reproductive system including pregnancy-related diseases, gynecologic cancers, and endometriosis. In conclusion, there is no denying that circRNAs have immense potential to be used as biomarkers and treatments for reproductive disorders in males and females. In this research, we provide a comprehensive analysis of the multiple circRNAs associated with women's infertility.

Transcriptomic effects of alginate hydrogel applied to the production of bovine embryos

In vitro-produced blastocysts are exposed to different stimuli when compared with in vivo ones. This includes the culture of in vitro embryos in a sturdy petri-dish, while in vivo embryos develop in a soft and dynamic structure. Here we hypothesized that a softer environment could differently modulate the in vitro produced embryos. To that aim, presumptive zygotes were produced by in vitro fertilization and divided into three groups: 1) Cultured in a regular Petri dish - Control (CON); 2) Cultured on top of an alginate hydrogel surface (TOP); 3) Encapsulated inside an alginate hydrogel sphere (ENC) and cultured. We observed a decrease in blastocyst rate in TOP and ENC compared with the CON. Profiling of 383 bovine miRNAs, we found 3 miRNAs involved in cell proliferation being differently modulated by the TOP and ENC groups (miR-1246; miR-1260b, and miR-541). Analyzing global levels of DNA methylation and hydroxymethylation, we observed increased levels of the two marks in the TOP group when compared with the CON and ENC systems. RNA sequencing (RNA-seq) analysis carried out using blastocysts showed alterations in several developmentally important genes among the three groups. In summary, our results indicate that in vitro embryo production was possible to achieve up to the blastocyst stage. However, with the experimental conditions used herein, the alginate hydrogels adversely affected the embryo development, which were paralleled by epigenetic and transcriptomic changes.

Mesenchymal Traits as an Intrinsic Feature of Undifferentiated Cells

Since its first conceptualization over a century ago, the mesenchymal phenotype has traditionally been viewed as either a transient phase between successive epithelial stages or as a feature of cell types primarily devoted to structural support. However, recent findings in cancer research challenge this limited view, demonstrating that mesenchymal traits and hybrid mesenchymal/epithelial states can mark cancer cells with stem cell properties. By analyzing publicly available single-cell transcriptome datasets from early embryonic stages and adult tissues, this study aims to extend this concept beyond pathological contexts, suggesting that a partial or fully mesenchymal phenotype may represent the morphological expression of undifferentiated and multipotent states in both the developing embryo and adult organs.

Complex aneuploidy triggers autophagy and p53-mediated apoptosis and impairs the second lineage segregation in human preimplantation embryos

About 70% of human cleavage stage embryos show chromosomal mosaicism, falling to 20% in blastocysts. Chromosomally mosaic human blastocysts can implant and lead to healthy new-borns with normal karyotypes. Studies in mouse embryos and human gastruloids showed that aneuploid cells are eliminated from the epiblast by p53-mediated apoptosis while being tolerated in the trophectoderm. These observations suggest a selective loss of aneuploid cells from human embryos, but the underlying mechanisms are not yet fully understood. Here, we investigated the cellular consequences of aneuploidy in a total of 125 human blastocysts. RNA-sequencing of trophectoderm cells showed activated p53 pathway and apoptosis proportionate to the level of chromosomal imbalance. Immunostaining corroborated that aneuploidy triggers proteotoxic stress, autophagy, p53-signaling, and apoptosis independent from DNA damage. Total cell numbers were lower in aneuploid embryos, due to a decline both in trophectoderm and in epiblast/primitive endoderm cell numbers. While lower cell numbers in trophectoderm may be attributed to apoptosis, aneuploidy impaired the second lineage segregation, particularly primitive endoderm formation. This might be reinforced by retention of NANOG. Our findings might explain why fully aneuploid embryos fail to further develop and we hypothesize that the same mechanisms lead to the removal of aneuploid cells from mosaic embryos.

Single nucleotide polymorphisms are associated with strain-specific virulence differences among clinical isolates of Cryptococcus neoformans

Studies across various pathogens highlight the importance of pathogen genetic differences in disease manifestation. In the human fungal pathogen Cryptococcus neoformans, sequence type (ST) associates with patient outcome. We performed a meta-analysis of four genomic studies and identified overlapping gene regions associated with virulence, suggesting the importance of these gene regions in cryptococcal disease in diverse clinical isolates. We explored the relationship between virulence and strain genetic differences using the cryptococcosis mouse model and a closely related library of ST93 clinical isolates. We identified four in vivo virulence phenotypes: hypervirulence, typical virulence with CNS disease, typical virulence with non-CNS disease, and latent disease. Hypervirulent isolates were clade specific and associated with an interferon gamma (IFNγ) dominated immune response. Using a genome wide association study (GWAS), we identified nine genes with polymorphisms associated with IFNγ production, including the inositol sensor ITR4. The itr4Δ mutant recapitulated the hypervirulence phenotype and ITR4 affects expression of two IFNγ associated genes. Finally, we showed that IFNγ production is associated with SNPs that downregulate ITR4 and with SNP accumulation in other IFNγ associated genes. These data highlight the complex role of pathogen genetics in virulence and identify genes associated with hypervirulence and IFNγ in Cryptococcus neoformans.

The impact of retrotransposons on zygotic genome activation and the chromatin landscape of early embryos

In mammals, fertilization is followed by extensive reprogramming and reorganization of the chromatin accompanying the transcriptional activation of the embryo. This reprogramming results in blastomeres with the ability to give rise to all cell types and a complete organism, including extra-embryonic tissues, and is known as totipotency. Transcriptional activation occurs in a process known as zygotic genome activation (ZGA) and is tightly linked to the expression of transposable elements, including endogenous retroviruses (ERVs) such as endogenous retrovirus with leucine tRNA primer (ERVL). Recent studies discovered the importance of ERVs in this process, yet the race to decipher the network surrounding these elements is still ongoing, and the molecular mechanism behind their involvement remains a mystery. Amid a recent surge of studies reporting the discovery of various factors and pathways involved in the regulation of ERVs, this review provides an overview of the knowns and unknowns in the field, with a particular emphasis on the chromatin landscape and how ERVs shape preimplantation development in mammals. In so doing, we highlight recent discoveries that have advanced our understanding of how these elements are involved in transforming the quiescent zygote into the most powerful cell type in mammals.

Single-cell RNA sequencing offers opportunities to explore the depth of physiology, adaptation, and biochemistry in non-model organisms exposed to pollution

Single-cell Sequencing technology (scSeq) has revolutionized our understanding of individual cells, uncovering unprecedented heterogeneity within tissues and cell populations, principality through single-cell RNA Sequencing (scRNA-Seq). This short review highlights the pivotal role of scRNA-Seq in elucidating genotype-phenotype relationships, particularly in biological systems. Based on published articles, our analysis involved manual curation and automated Scopus tools to illustrate recent advances in the application of scRNA-Seq. The results reveal that scRNA-Seq has been extensively utilized in various biological areas, including biochemistry, genetics, molecular biology, immunology, and microbiology, followed by health sciences covering studies related to the nervous system, immune system, human health, development, and diseases, with a particular focus on cancer research. However, the potential of scRNA-Seq extends beyond disease research, offering insights into non-model organisms' responses to environmental contaminants. By enabling the study of cellular reactions at a molecular level, scRNA-Seq provides a comprehensive understanding of intracellular heterogeneity that enhances our comprehension of physiological, biochemical, and pathological environmental impacts on non-model organisms exposed to pollution. This understanding has many practical benefits, as it can aid in regulation and conservation efforts that benefit the environment and the use of economically essential and ecologically relevant organisms.

Multi-omics PGT: re-evaluation of euploid blastocysts for implantation potential based on RNA sequencing

STUDY QUESTION

In addition to chromosomal euploidy, can the transcriptome of blastocysts be used as a novel predictor of embryo implantation potential?

SUMMARY ANSWER

This retrospective analysis showed that based on differentially expressed genes (DEGs) between euploid blastocysts which resulted and did not result in a clinical pregnancy, machine learning models could help improve implantation rates by blastocyst optimization.

WHAT IS KNOWN ALREADY

Embryo implantation is a multifaceted process, with implantation loss and pregnancy failure related not only to blastocyst euploidy but also to the intricate dialog between blastocyst and endometrium. Although in vitro studies have revealed the characteristics of trophectoderm (TE) differentiation in implanted blastocysts and the function of TE placentation at the implantation site, the precise molecular mechanisms of embryo implantation and their clinical application remain to be fully elucidated.

STUDY DESIGN, SIZE, DURATION

This study involved 102 patients who underwent 111 cycles for preimplantation genetic testing for aneuploidies (PGT-A) between March 2022 and July 2023.

PARTICIPANTS/MATERIALS, SETTING, METHODS

The study included 412 blastocysts biopsied at Day 5 [D5] or Day 6 [D6] for patients who underwent PGT-A. The biopsy lysates were split and subjected to DNA and RNA sequencing (DNA- and RNA-seq). One part was used for PGT-A to detect DNA copy number variations, whereas the other part was assessed simultaneously by RNA-seq to determine the transcriptome characteristics. To validate the reliability and accuracy of RNA-seq obtained from this strategy, we initially analyzed the transcriptome of blastocysts with chromosomal aneuploidies. Subsequently, we compared the transcriptomic features of blastocysts with different rates of formation (D5 vs D6) and investigated the network of interactions between key blastulation genes and the receptive endometrium. Then to evaluate the implantation potential of euploid blastocysts, we identified DEGs between euploid blastocysts that resulted in clinical pregnancy (defined as the presence of a gestational sac detected by ultrasound after 5 weeks) and those that did not. These DEGs were then employed to construct a predictive model for optimizing blastocyst selection.

MAIN RESULTS AND THE ROLE OF CHANCE

The successful detection rate of PGT-A was remarkably high at 99.8%. The RNA data may infer aneuploidy for both trisomy and monosomy. Between the euploid blastocysts that formed on D5 and D6, 187 DEGs were predominantly involved in cell differentiation for embryonic placenta development, the PPAR signaling pathway, and the Notch signaling pathway. These D5/D6 DEGs also exhibited a functional dialog with the receptive phase endometrium-specific genes through protein-protein interaction networks, indicating that the embryo undergoes further differentiation for post-implantation development. Furthermore, a modeling strategy using 280 DEGs between blastocysts leading to successful clinical pregnancies or failing to produce clinical pregnancies was implemented to refine the euploid embryo optimization, achieving areas under the curves of 0.88, 0.71, and 0.84 for the random forest (RF), support vector machine, and linear discriminant analysis models, respectively. Finally, a retrospective analysis of 83 transferred euploid blastocysts using the RF model identified three types of euploid embryos with a decreasing trend in implantation potential. Notably, the implantation rate of the good group was significantly higher than that of the moderate group (88.6% vs 50.0% P = 0.001) and that of the moderate group was higher than that of the poor group (50.0% vs 20.8%, P = 0.035).

LIMITATIONS, REASONS FOR CAUTION

The sample size was insufficient; thus, a prospective study is needed to verify the clinical effectiveness of the above model. Because we did not analyze blastocysts that led only to biochemical pregnancies but failed clinical pregnancies separately, our classification system still must be modified to screen these embryos.

WIDER IMPLICATIONS OF THE FINDINGS

Transcriptomic analysis of blastocysts offers a novel approach for predicting embryo implantation potential, which can be utilized to optimize clinical embryo selection. The ranking system may be effective in reducing the times and costs involved in achieving a clinical pregnancy.

STUDY FUNDING/COMPETING INTEREST(S)

This study was funded by the "Pioneer" and "Leading Goose" R&D Program of Zhejiang (No. 2023C03034), the National Natural Science Foundation of China (82101709), and the National Key Research and Development Program for Young Scientists of China (No. 2022YFC2702300). The authors state no competing interests.

TRIAL REGISTRATION NUMBER

N/A.

In vitro culture of cynomolgus monkey embryos from blastocyst to early organogenesis

Human early embryonic development is the cornerstone of a healthy baby. Abnormal early embryonic development may lead to developmental and pregnancy-related disorders. Accordingly, understanding the developmental events and mechanisms of human early embryonic development is very important. However, attempts to reveal these events and mechanisms are greatly hindered by the extreme inaccessibility of in vivo early human embryos. Fortunately, the emergence of in vitro culture (IVC) systems for mammalian embryos provides an alternative strategy. In recent years, different two-dimensional and three-dimensional IVC systems have been developed for human embryos. Ethical limitations restrict the IVC of human embryos beyond 14 days, which makes non-human primate embryos an ideal model for studying primate developmental events. Different culture systems have supported the development of monkey embryos to days postfertilization 14 and 25, respectively. The successful recapitulation of in vivo developmental events by these IVC embryos has greatly enriched our understanding of human early embryonic development, which undoubtedly helps us to develop possible strategies to predict or treat various gestation-related diseases and birth defects. In this protocol, we establish different two-dimensional and three-dimensional IVC systems for primate embryos, provide step-by-step culture procedures and notes, and summarize the advantages and limitations of different culture systems. Replicating this protocol requires a moderate level of experience in mammalian embryo IVC, and the embryo culture requires strict adherence to the procedures we have described.

scQA: A dual-perspective cell type identification model for single cell transcriptome data

Single-cell RNA sequencing technologies have been pivotal in advancing the development of algorithms for clustering heterogeneous cell populations. Existing methods for utilizing scRNA-seq data to identify cell types tend to neglect the beneficial impact of dropout events and perform clustering focusing solely on quantitative perspective. Here, we introduce a novel method named scQA, notable for its ability to concurrently identify cell types and cell type-specific key genes from both qualitative and quantitative perspectives. In contrast to other methods, scQA not only identifies cell types but also extracts key genes associated with these cell types, enabling bidirectional clustering for scRNA-seq data. Through an iterative process, our approach aims to minimize the number of landmarks to approximately a dozen while maximizing the inclusion of quasi-trend-preserved genes with dropouts both qualitatively and quantitatively. It then clusters cells by employing an ingenious label propagation strategy, obviating the requirement for a predetermined number of cell types. Validated on 20 publicly available scRNA-seq datasets, scQA consistently outperforms other salient tools. Furthermore, we confirm the effectiveness and potential biological significance of the identified key genes through both external and internal validation. In conclusion, scQA emerges as a valuable tool for investigating cell heterogeneity due to its distinctive fusion of qualitative and quantitative facets, along with bidirectional clustering capabilities. Furthermore, it can be seamlessly integrated into border scRNA-seq analyses. The source codes are publicly available at https://github.com/LD-Lyndee/scQA.

A novel human protein-coding locus identified using a targeted RNA enrichment technique

BACKGROUND

Accurate and comprehensive genomic annotation, including the full list of protein-coding genes, is vital for understanding the molecular mechanisms of human biology. We have previously shown that the genome contains a multitude of yet hidden functional exons and transcripts, some of which might represent novel mRNAs. These results resonate with those from other groups and strongly argue that two decades after the completion of the first draft of the human genome sequence, the current annotation of human genes and transcripts remains far from being complete.

RESULTS

Using a targeted RNA enrichment technique, we showed that one of the novel functional exons previously discovered by us and currently annotated as part of a long non-coding RNA, is actually a part of a novel protein-coding gene, InSETG-4, which encodes a novel human protein with no known homologs or motifs. We found that InSETG-4 is induced by various DNA-damaging agents across multiple cell types and therefore might represent a novel component of DNA damage response. Despite its low abundance in bulk cell populations, InSETG-4 exhibited expression restricted to a small fraction of cells, as demonstrated by the amplification-based single-molecule fluorescence in situ hybridization (asmFISH) analysis.

CONCLUSIONS

This study argues that yet undiscovered human protein-coding genes exist and provides an example of how targeted RNA enrichment techniques can help to fill this major gap in our knowledge of the information encoded in the human genome.

Transcriptomic profiling of day 3 human embryos of poor quality reveals molecular links to divergent developmental trajectories

Poor-quality (PQ) embryos are commonly formed in assisted reproduction and often discarded, but emerging evidence suggests that some can develop into healthy children. Here, we performed single-embryo transcriptome profiling of day 3 human embryos of both good quality (GQ) and PQ. Our analyses revealed that day 3 PQ embryos can be categorized into two distinct subgroups: genuine PQ (gPQ) and morphological PQ (mPQ) embryos. This was further supported by additional transcriptomic data of GQ and PQ embryos donated by the same individuals. gPQ embryos showed greater impairments in both RNA decay and zygotic genome activation (ZGA) compared to mPQ embryos. Blastocysts that emerged from PQ embryos, more likely from mPQ embryos, demonstrated transcriptomic similarity to normal blastocysts. We also identified genes highly upregulated in day 3 gPQ embryos. These molecular insights may improve embryo selection and offer valuable clues for enhancing embryo quality in the future.

FunlncModel: integrating multi-omic features from upstream and downstream regulatory networks into a machine learning framework to identify functional lncRNAs

Accumulating evidence indicates that long noncoding RNAs (lncRNAs) play important roles in molecular and cellular biology. Although many algorithms have been developed to reveal their associations with complex diseases by using downstream targets, the upstream (epi)genetic regulatory information has not been sufficiently leveraged to predict the function of lncRNAs in various biological processes. Therefore, we present FunlncModel, a machine learning-based interpretable computational framework, which aims to screen out functional lncRNAs by integrating a large number of (epi)genetic features and functional genomic features from their upstream/downstream multi-omic regulatory networks. We adopted the random forest method to mine nearly 60 features in three categories from >2000 datasets across 11 data types, including transcription factors (TFs), histone modifications, typical enhancers, super-enhancers, methylation sites, and mRNAs. FunlncModel outperformed alternative methods for classification performance in human embryonic stem cell (hESC) (0.95 Area Under Curve (AUROC) and 0.97 Area Under the Precision-Recall Curve (AUPRC)). It could not only infer the most known lncRNAs that influence the states of stem cells, but also discover novel high-confidence functional lncRNAs. We extensively validated FunlncModel's efficacy by up to 27 cancer-related functional prediction tasks, which involved multiple cancer cell growth processes and cancer hallmarks. Meanwhile, we have also found that (epi)genetic regulatory features, such as TFs and histone modifications, serve as strong predictors for revealing the function of lncRNAs. Overall, FunlncModel is a strong and stable prediction model for identifying functional lncRNAs in specific cellular contexts. FunlncModel is available as a web server at https://bio.liclab.net/FunlncModel/.

Understanding isoform expression by pairing long-read sequencing with single-cell and spatial transcriptomics

RNA isoform diversity, produced via alternative splicing, and alternative usage of transcription start and poly(A) sites, results in varied transcripts being derived from the same gene. Distinct isoforms can play important biological roles, including by changing the sequences or expression levels of protein products. The first single-cell approaches to RNA sequencing-and later, spatial approaches-which are now widely used for the identification of differentially expressed genes, rely on short reads and offer the ability to transcriptomically compare different cell types but are limited in their ability to measure differential isoform expression. More recently, long-read sequencing methods have been combined with single-cell and spatial technologies in order to characterize isoform expression. In this review, we provide an overview of the emergence of single-cell and spatial long-read sequencing and discuss the challenges associated with the implementation of these technologies and interpretation of these data. We discuss the opportunities they offer for understanding the relationships between the distinct variable elements of transcript molecules and highlight some of the ways in which they have been used to characterize isoforms' roles in development and pathology. Single-nucleus long-read sequencing, a special case of the single-cell approach, is also discussed. We attempt to cover both the limitations of these technologies and their significant potential for expanding our still-limited understanding of the biological roles of RNA isoforms.

mTOR activity paces human blastocyst stage developmental progression

Many mammals can temporally uncouple conception from parturition by pacing down their development around the blastocyst stage. In mice, this dormant state is achieved by decreasing the activity of the growth-regulating mTOR signaling pathway. It is unknown whether this ability is conserved in mammals in general and in humans in particular. Here, we show that decreasing the activity of the mTOR signaling pathway induces human pluripotent stem cells (hPSCs) and blastoids to enter a dormant state with limited proliferation, developmental progression, and capacity to attach to endometrial cells. These in vitro assays show that, similar to other species, the ability to enter dormancy is active in human cells around the blastocyst stage and is reversible at both functional and molecular levels. The pacing of human blastocyst development has potential implications for reproductive therapies.

LncRNA mediated metabolic reprogramming: the chief culprits of solid tumor malignant progression: an update review

Metabolism reprogramming (MR) is one of the top ten hallmarks of malignant tumors. The aberrant activation of MR has been recognized as a critical contributory factor to the malignant progression of solid tumors. Moreover, various long non-coding RNAs (lncRNAs) are implicated in the aberrant activation of MR in solid tumor cells. Therefore, in this review, we mainly focus on summarizing the functional relevance and molecular mechanistic underpinnings of lncRNAs in modulating MR of solid tumors by targeting glucose metabolism, lipid metabolism, affecting mitochondrial function, and regulating interactions between tumor and non-tumor cells in tumor microenvironment. Besides, we also underscore the potential for constructing lncRNAs-centered tumor metabolic regulation networks and developing novel anti-tumor strategies by targeting lncRNAs and abnormal MR. Ultimately, this review seeks to offer new targets and avenues for the clinical treatment of solid tumors in the future.

Combining single-cell profiling and functional analysis explores the role of pseudogenes in human early embryonic development

More and more studies have demonstrated that pseudogenes possess coding ability, and the functions of their transcripts in the development of diseases have been partially revealed. However, the role of pseudogenes in maintenance of normal physiological states and life activities has long been neglected. Here, we identify pseudogenes that are dynamically expressed during human early embryogenesis, showing different expression patterns from that of adult tissues. We explore the expression correlation between pseudogenes and the parent genes, partly due to their shared gene regulatory elements or the potential regulation network between them. The essential role of three pseudogenes, PI4KAP1, TMED10P1, and FBXW4P1, in maintaining self-renewal of human embryonic stem cells is demonstrated. We further find that the three pseudogenes might perform their regulatory functions by binding to proteins or microRNAs. The pseudogene-related single-nucleotide polymorphisms are significantly associated with human congenital disease, further illustrating their importance during early embryonic development. Overall, this study is an excavation and exploration of functional pseudogenes during early human embryonic development, suggesting that pseudogenes are not only capable of being specifically activated in pathological states, but also play crucial roles in the maintenance of normal physiological states.

CHK1 controls zygote pronuclear envelope breakdown by regulating F-actin through interacting with MICAL3

CHK1 mutations could cause human zygote arrest at the pronuclei stage, a phenomenon that is not well understood at the molecular level. In this study, we conducted experiments where pre-pronuclei from zygotes with CHK1 mutation were transferred into the cytoplasm of normal enucleated fertilized eggs. This approach rescued the zygote arrest caused by the mutation, resulting in the production of a high-quality blastocyst. This suggests that CHK1 dysfunction primarily disrupts crucial biological processes occurring in the cytoplasm. Further investigation reveals that CHK1 mutants have an impact on the F-actin meshwork, leading to disturbances in pronuclear envelope breakdown. Through co-immunoprecipitation and mass spectrometry analysis of around 6000 mouse zygotes, we identified an interaction between CHK1 and MICAL3, a key regulator of F-actin disassembly. The gain-of-function mutants of CHK1 enhance their interaction with MICAL3 and increase MICAL3 enzymatic activity, resulting in excessive depolymerization of F-actin. These findings shed light on the regulatory mechanism behind pronuclear envelope breakdown during the transition from meiosis to the first mitosis in mammals.

Decrypting the viral community in aerobic activated sludge reactors treating antibiotic production wastewater

Viruses are the most abundant yet understudied members that may influence microbial metabolism in activated sludge treating antibiotic production wastewater. This study comprehensively investigated virome community characteristics under the selection pressure of nine types and different concentrations of antibiotics using a metagenomics approach. Of the 15,514 total viral operational taxonomic units (tOTUs) recovered, only 37.5 % were annotated. Antibiotics altered the original viral community structure in activated sludge. The proportion of some pathogenic viral families, including Herpesviridae_like, increased significantly in reactors treating erythromycin production wastewater. In total, 16.5 % of the tOTUs were associated with two or more hosts. tOTUs rarely carried antibiotic resistance genes (ARGs), and the ARG types in the tOTUs did not match the ARGs carried by the bacterial hosts. This suggests that transduction contributes little to the horizontal ARG transfer. Auxiliary metabolic genes (AMGs) were prevalent in tOTUs, and those involved in folate biosynthesis were particularly abundant, indicating their potential to mitigate antibiotic-induced host damage. This study provides comprehensive insights into the virome community in activated sludge treating antibiotic production wastewater and sheds light on the potential role of viral AMGs in mitigating antibiotic-induced stress.

Profiling the transcriptomic age of single-cells in humans

Although aging clocks predicting the age of individual organisms have been extensively studied, the age of individual cells remained largely unexplored. Most recently single-cell omics clocks were developed for the mouse, however, extensive profiling the age of human cells is still lacking. To fill this gap, here we use available scRNA-seq data of 1,058,909 blood cells of 508 healthy, human donors (between 19 and 75 years), for developing single-cell transcriptomic clocks and predicting the age of human blood cells. By the application of the proposed cell-type-specific single-cell clocks, our main observations are that (i) transcriptomic age is associated with cellular senescence; (ii) the transcriptomic age of classical monocytes as well as naive B and T cells is decreased in moderate COVID-19 followed by an increase for some cell types in severe COVID-19; and (iii) the human embryo cells transcriptomically rejuvenated at the morulae and blastocyst stages. In summary, here we demonstrate that single-cell transcriptomic clocks are useful tools to investigate aging and rejuvenation at the single-cell level.

The Role of Long Intergenic Noncoding RNA in Fetal Development

The role of long intergenic noncoding RNAs (lincRNAs) in fetal development has emerged as a significant area of study, challenging the traditional protein-centric view of gene expression. While messenger RNAs (mRNAs) have long been recognized for their role in encoding proteins, recent advances have illuminated the critical functions of lincRNAs in various biological processes. Initially identified through high-throughput sequencing technologies, lincRNAs are transcribed from intergenic regions between protein-coding genes and exhibit unique regulatory functions. Unlike mRNAs, lincRNAs are involved in complex interactions with chromatin and chromatin-modifying complexes, influencing gene expression and chromatin structure. LincRNAs are pivotal in regulating tissue-specific development and embryogenesis. For example, they are crucial for proper cardiac, neural, and reproductive system development, with specific lincRNAs being associated with organogenesis and differentiation processes. Their roles in embryonic development include regulating transcription factors and modulating chromatin states, which are essential for maintaining developmental programs and cellular identity. Studies using RNA sequencing and genetic knockout models have highlighted the importance of lincRNAs in processes such as cell differentiation, tissue patterning, and organ development. Despite their functional significance, the comprehensive annotation and understanding of lincRNAs remain limited. Ongoing research aims to elucidate their mechanisms of action and potential applications in disease diagnostics and therapeutics. This review summarizes current knowledge on the functional roles of lincRNAs in fetal development, emphasizing their contributions to tissue-specific gene regulation and developmental processes.

Enormous diversity of RNA viruses in economic crustaceans

Crustaceans are important food sources worldwide and possess significant ecological status in the marine ecosystem. However, our understanding of the diversity and evolution of RNA viruses in crustaceans, especially in economic crustaceans, is still limited. Here, 106 batches of economic crustaceans including 13 species were collected from 24 locations in China during 2016-2021. We identified 90 RNA viruses, 69 of which were divergent from the known viruses. Viral transcripts were assigned to 18 different viral families/clades and three unclassified groups. Among the identified viruses, five were double-stranded RNA viruses, 74 were positive-sense single-stranded RNA (+ssRNA) viruses, nine were negative-sense single-stranded RNA (-ssRNA) viruses, and two belonged to an unclassified RNA virus group. Phylogenetic analyses showed that crustacean viruses were often clustered with viruses identified from invertebrates. Remarkably, most crustacean viruses were closely related to those from different host species along the same food chain or ecological aquatic niche. In addition, the genome structures of the newly discovered picornaviruses exhibited remarkable diversity. Our study significantly expands the diversity of viruses in important economic crustaceans and provides essential data for the risk assessment of the pathogens spreading in the global aquaculture industry.

IMPORTANCE

The study delves into the largely uncharted territory of RNA viruses in crustaceans, which are not only vital for global food supply but also play a pivotal role in marine ecosystems. Focusing on economic crustaceans, the research uncovers 90 RNA viruses, with 69 being potentially new to science, highlighting the vast unknown viral diversity within these marine organisms. The findings reveal that these viruses are often related to those found in other invertebrates and tend to share close relationships with viruses from species within the same food web or habitat. This suggests that viruses may move between different marine species more frequently than previously thought. The discovery of such a wide variety of viruses, particularly the diverse genome structures of newly identified picornaviruses, is a significant leap forward in understanding the crustacean virology. This knowledge is crucial for managing disease risks in aquaculture and maintaining the balance of marine ecosystems.

Elucidation of the pluripotent potential of bovine embryonic lineages facilitates the establishment of formative stem cell lines

The establishment of epiblast-derived pluripotent stem cells (PSCs) from cattle, which are important domestic animals that provide humans with milk and meat while also serving as bioreactors for producing valuable proteins, poses a challenge due to the unclear molecular signaling required for embryonic epiblast development and maintenance of PSC self-renewal. Here, we selected six key stages of bovine embryo development (E5, E6, E7, E10, E12, and E14) to track changes in pluripotency and the dependence on signaling pathways via modified single-cell transcription sequencing technology. The remarkable similarity of the gene expression patterns between cattle and pigs during embryonic lineage development contributed to the successful establishment of bovine epiblast stem cells (bEpiSCs) using 3i/LAF (WNTi, GSK3βi, SRCi, LIF, Activin A, and FGF2) culture system. The generated bEpiSCs exhibited consistent expression patterns of formative epiblast pluripotency genes and maintained clonal morphology, normal karyotypes, and proliferative capacity for more than 112 passages. Moreover, these cells exhibited high-efficiency teratoma formation as well as the ability to differentiate into various cell lineages. The potential of bEpiSCs for myogenic differentiation, primordial germ cell like cells (PGCLCs) induction, and as donor cells for cell nuclear transfer was also assessed, indicating their promise in advancing cell-cultured meat production, gene editing, and animal breeding.

Inhibition of neddylation disturbs zygotic genome activation through histone modification change and leads to early development arrest in mouse embryos

Post-translational modification and fine-tuned protein turnover are of great importance in mammalian early embryo development. Apart from the classic protein degradation promoting ubiquitination, new forms of ubiquitination-like modification are yet to be fully understood. Here, we demonstrate the function and potential mechanisms of one ubiquitination-like modification, neddylation, in mouse preimplantation embryo development. Treated with specific inhibitors, zygotes showed a dramatically decreased cleavage rate and almost all failed to enter the 4-cell stage. Transcriptional profiling showed genes were differentially expressed in pathways involving cell fate determination and cell differentiation, including several down-regulated zygotic genome activation (ZGA) marker genes. A decreased level of phosphorylated RNA polymerase II was detected, indicating impaired gene transcription inside the embryo cell nucleus. Proteomic data showed that differentially expressed proteins were enriched in histone modifications. We confirmed the lowered in methyltransferase (KMT2D) expression and a decrease in histone H3K4me3. At the same time, acetyltransferase (CBP/p300) reduced, while deacetylase (HDAC6) increased, resulting in an attenuation in histone H3K27ac. Additionally, we observed the up-regulation in YAP1 and RPL13 activities, indicating potential abnormalities in the downstream response of Hippo signaling pathway. In summary, we found that inhibition of neddylation induced epigenetic changes in early embryos and led to abnormalities in related downstream signaling pathways. This study sheds light upon new forms of ubiquitination regulating mammalian embryonic development and may contribute to further investigation of female infertility pathology.

New insights into oocyte cytoplasmic lattice-associated proteins

Oocyte maturation and preimplantation embryo development are critical to successful pregnancy outcomes and the correct establishment and maintenance of genomic imprinting. Thanks to novel technologies and omics studies in human patients and mouse models, the importance of the proteins associated with the cytoplasmic lattices (CPLs), highly abundant structures found in the cytoplasm of mammalian oocytes and preimplantation embryos, in the maternal to zygotic transition is becoming increasingly evident. This review highlights the recent discoveries on the role of these proteins in protein storage and other oocyte cytoplasmic processes, epigenetic reprogramming, and zygotic genome activation (ZGA). A better comprehension of these events may significantly improve clinical diagnosis and pave the way for targeted interventions aiming to correct or mitigate female fertility issues and genomic imprinting disorders.

Protein Modifications During Early Embryo Development

BACKGROUND

Infertility is a global reproductive health burden. Assisted reproductive technologies (ARTs) have been widely used to help patients become pregnant. Few embryos develop to the blastocyst stage with ARTs, leading to relatively low live birth rates. Protein modifications play crucial roles in nearly every aspect of cell biology, including reproductive processes. The aim of this study was to explore the characteristics of protein modifications during embryonic development.

METHODS

Proteomic data from humans and mice were acquired from the integrated proteome resources (iProX) of ProteomeXchange (PXD024267) and a tandem mass tag (TMT)-mass spectrometry dataset. Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were applied for functional annotation. Protein-protein interactions (PPIs) of the modification-related genes were revealed by the STRING database. Modified proteins during mouse embryogenesis were visualized through heatmaps of hierarchically clustering using k-means.

RESULTS

We identified modification-related proteins in human embryo development and characterized them through heatmaps, GO analysis, KEGG analysis, and PPI network analysis. We found that the 4-cell stage to the 8-cell stage might be the demarcation period for modification-related protein expression patterns during embryo development. Using quantitative mass spectrometry, we elucidated the methylation, acetylation, and ubiquitination events that occur during mouse embryogenesis to validate our findings in human embryonic development to some extent.

CONCLUSIONS

The results of our study suggest that the posttranslational modifications (PTMs) of human preimplantation embryos might exhibit the same trends as those in mice to exert synergistic and fine-tuned regulatory effects during embryonic development.

Anoikis in cell fate, physiopathology, and therapeutic interventions

The extracellular matrix (ECM) governs a wide spectrum of cellular fate processes, with a particular emphasis on anoikis, an integrin-dependent form of cell death. Currently, anoikis is defined as an intrinsic apoptosis. In contrast to traditional apoptosis and necroptosis, integrin correlates ECM signaling with intracellular signaling cascades, describing the full process of anoikis. However, anoikis is frequently overlooked in physiological and pathological processes as well as traditional in vitro research models. In this review, we summarized the role of anoikis in physiological and pathological processes, spanning embryonic development, organ development, tissue repair, inflammatory responses, cardiovascular diseases, tumor metastasis, and so on. Similarly, in the realm of stem cell research focused on the functional evolution of cells, anoikis offers a potential solution to various challenges, including in vitro cell culture models, stem cell therapy, cell transplantation, and engineering applications, which are largely based on the regulation of cell fate by anoikis. More importantly, the regulatory mechanisms of anoikis based on molecular processes and ECM signaling will provide new strategies for therapeutic interventions (drug therapy and cell-based therapy) in disease. In summary, this review provides a systematic elaboration of anoikis, thus shedding light on its future research.

The role of the ceRNA network mediated by lncRNA SNHG3 in the progression of cancer

BACKGROUND

Long non-coding RNAs (lncRNAs) are a distinct class of RNAs with longer than 200 base pairs that are not translated into proteins. Small Nucleolar RNA Host Gene 3 (SNHG3) is a lncRNA and frequently dysregulated in various human cancers.

OBJECTIVE

This review provides a comprehensive analysis of current research on lncRNA SNHG3, focusing on its role within the competitive endogenous RNA (ceRNA) network and its implications in cancer.

METHODS

A systematic literature review was conducted using PubMed up to October 2023. The search strategy included keywords such as "lncRNA SNHG3", "competitive endogenous RNA", "cancer", and related terms. Studies were selected based on relevance to SNHG3's involvement in cancer pathogenesis and progression.

RESULTS

Disruptions in the ceRNA network involving lncRNA SNHG3 can impair normal cell growth and differentiation, significantly contributing to disease pathogenesis, particularly cancer. This review highlights SNHG3's substantial impact on various cancer processes and its potential as a diagnostic and therapeutic tool for aggressive cancers.

CONCLUSION

The findings underscore SNHG3's pivotal role in cancer prevention, diagnosis, and treatment, laying a foundation for future research in cancer management. Insights from this review emphasize the necessity for further exploration and development of SNHG3-based diagnostic and therapeutic strategies.

A Journey through the Minefield of the Discovery and Characterization of Latency-Related RNA/Latency-Associated Transcript

Scientific knowledge evolves in small steps, with occasional backsteps to correct inaccuracies, all occurring within a competitive environment. This perspective for the first time looks at the history of latency-related RNA (LR-RNA) that was later renamed latency-associated transcript (LAT). At the 1986 International Herpesvirus Workshop (IHW) meeting in Leeds, England, Daniel L Rock and Anthony B Nesburn first reported the discovery of human herpes virus 1 (HSV-1) latency-related (LR) RNA that is antisense to ICP0. Less than a month after the IHW meeting, a paper was submitted to Science magazine and 8 months later appeared in print thanking "D. Rock for suggesting RNA complementary to the ICP0 message may be present in latently infected cells". This perspective is not a review of the LAT literature but intends to clarify the timeline of LAT discovery and subsequent breakthroughs such as reactivation, apoptosis, CD8+ T cell exhaustion, and LAT expression in different cell types detected during latency. While many review articles have been written about LAT since 1987, the most comprehensive and balanced review about LAT was written by Dr. David Bloom's group. In this overview, I will discuss our original collaboration with Dr. Dan Rock and subsequent work that our group performed, which is still ongoing. Finally, I will discuss the controversies associated with LAT from its inception to current times.

Metabolic regulation of preimplantation embryo development in vivo and in vitro: Molecular mechanisms and insights

Understanding of embryonic development has led to the clinical application of Assisted Reproductive technologies (ART), with the resulting birth of millions of children. Recent developments in metabolomics, proteomics, and transcriptomics have brought to light new insights into embryonic growth dynamics, with implications spanning reproductive medicine, stem cell research, and regenerative medicine. The review explores the key metabolic processes and molecular pathways active during preimplantation embryo development, including PI3K-Akt, mTOR, AMPK, Wnt/β-catenin, TGF-β, Notch and Jak-Stat signaling pathways. We focused on analyzing the differences occurring in vitro as opposed to in vivo development and we discussed significant physiological and clinical implications.

Identifying cell types by lasso-constraint regularized Gaussian graphical model based on weighted distance penalty

Single-cell RNA sequencing (scRNA-seq) technology is one of the most cost-effective and efficacious methods for revealing cellular heterogeneity and diversity. Precise identification of cell types is essential for establishing a robust foundation for downstream analyses and is a prerequisite for understanding heterogeneous mechanisms. However, the accuracy of existing methods warrants improvement, and highly accurate methods often impose stringent equipment requirements. Moreover, most unsupervised learning-based approaches are constrained by the need to input the number of cell types a prior, which limits their widespread application. In this paper, we propose a novel algorithm framework named WLGG. Initially, to capture the underlying nonlinear information, we introduce a weighted distance penalty term utilizing the Gaussian kernel function, which maps data from a low-dimensional nonlinear space to a high-dimensional linear space. We subsequently impose a Lasso constraint on the regularized Gaussian graphical model to enhance its ability to capture linear data characteristics. Additionally, we utilize the Eigengap strategy to predict the number of cell types and obtain predicted labels via spectral clustering. The experimental results on 14 test datasets demonstrate the superior clustering accuracy of the WLGG algorithm over 16 alternative methods. Furthermore, downstream analysis, including marker gene identification, pseudotime inference, and functional enrichment analysis based on the similarity matrix and predicted labels from the WLGG algorithm, substantiates the reliability of WLGG and offers valuable insights into biological dynamic biological processes and regulatory mechanisms.

Graph contrastive learning as a versatile foundation for advanced scRNA-seq data analysis

Single-cell RNA sequencing (scRNA-seq) offers unprecedented insights into transcriptome-wide gene expression at the single-cell level. Cell clustering has been long established in the analysis of scRNA-seq data to identify the groups of cells with similar expression profiles. However, cell clustering is technically challenging, as raw scRNA-seq data have various analytical issues, including high dimensionality and dropout values. Existing research has developed deep learning models, such as graph machine learning models and contrastive learning-based models, for cell clustering using scRNA-seq data and has summarized the unsupervised learning of cell clustering into a human-interpretable format. While advances in cell clustering have been profound, we are no closer to finding a simple yet effective framework for learning high-quality representations necessary for robust clustering. In this study, we propose scSimGCL, a novel framework based on the graph contrastive learning paradigm for self-supervised pretraining of graph neural networks. This framework facilitates the generation of high-quality representations crucial for cell clustering. Our scSimGCL incorporates cell-cell graph structure and contrastive learning to enhance the performance of cell clustering. Extensive experimental results on simulated and real scRNA-seq datasets suggest the superiority of the proposed scSimGCL. Moreover, clustering assignment analysis confirms the general applicability of scSimGCL, including state-of-the-art clustering algorithms. Further, ablation study and hyperparameter analysis suggest the efficacy of our network architecture with the robustness of decisions in the self-supervised learning setting. The proposed scSimGCL can serve as a robust framework for practitioners developing tools for cell clustering. The source code of scSimGCL is publicly available at https://github.com/zhangzh1328/scSimGCL.

scDFN: enhancing single-cell RNA-seq clustering with deep fusion networks

Single-cell ribonucleic acid sequencing (scRNA-seq) technology can be used to perform high-resolution analysis of the transcriptomes of individual cells. Therefore, its application has gained popularity for accurately analyzing the ever-increasing content of heterogeneous single-cell datasets. Central to interpreting scRNA-seq data is the clustering of cells to decipher transcriptomic diversity and infer cell behavior patterns. However, its complexity necessitates the application of advanced methodologies capable of resolving the inherent heterogeneity and limited gene expression characteristics of single-cell data. Herein, we introduce a novel deep learning-based algorithm for single-cell clustering, designated scDFN, which can significantly enhance the clustering of scRNA-seq data through a fusion network strategy. The scDFN algorithm applies a dual mechanism involving an autoencoder to extract attribute information and an improved graph autoencoder to capture topological nuances, integrated via a cross-network information fusion mechanism complemented by a triple self-supervision strategy. This fusion is optimized through a holistic consideration of four distinct loss functions. A comparative analysis with five leading scRNA-seq clustering methodologies across multiple datasets revealed the superiority of scDFN, as determined by better the Normalized Mutual Information (NMI) and the Adjusted Rand Index (ARI) metrics. Additionally, scDFN demonstrated robust multi-cluster dataset performance and exceptional resilience to batch effects. Ablation studies highlighted the key roles of the autoencoder and the improved graph autoencoder components, along with the critical contribution of the four joint loss functions to the overall efficacy of the algorithm. Through these advancements, scDFN set a new benchmark in single-cell clustering and can be used as an effective tool for the nuanced analysis of single-cell transcriptomics.

Clustering scRNA-seq data with the cross-view collaborative information fusion strategy

Single-cell RNA sequencing (scRNA-seq) technology has revolutionized biological research by enabling high-throughput, cellular-resolution gene expression profiling. A critical step in scRNA-seq data analysis is cell clustering, which supports downstream analyses. However, the high-dimensional and sparse nature of scRNA-seq data poses significant challenges to existing clustering methods. Furthermore, integrating gene expression information with potential cell structure data remains largely unexplored. Here, we present scCFIB, a novel information bottleneck (IB)-based clustering algorithm that leverages the power of IB for efficient processing of high-dimensional sparse data and incorporates a cross-view fusion strategy to achieve robust cell clustering. scCFIB constructs a multi-feature space by establishing two distinct views from the original features. We then formulate the cell clustering problem as a target loss function within the IB framework, employing a collaborative information fusion strategy. To further optimize scCFIB's performance, we introduce a novel sequential optimization approach through an iterative process. Benchmarking against established methods on diverse scRNA-seq datasets demonstrates that scCFIB achieves superior performance in scRNA-seq data clustering tasks. Availability: the source code is publicly available on GitHub: https://github.com/weixiaojiao/scCFIB.

Sperm-carried IGF2: towards the discovery of a spark contributing to embryo growth and development

Spermatozoa have been shown to carry key RNAs which, according to animal evidence, seem to play a role in early embryo development. In this context, a potential key growth regulator is insulin-like growth factor 2 (IGF2), a highly conserved paternally expressed imprinted gene involved in cell growth and proliferation which, recent observations indicate, is expressed in human spermatozoa. We herein hypothesized that sperm IGF2 gene expression and transmission at fertilization is required to support early embryo development. To test this hypothesis, we analyzed sperm IGF2 mRNA levels in the same semen aliquot used for homologous assisted reproductive technique (ART) in infertile couples and correlated these levels with embryo morphokinetics. To find a mechanistic explanation for the observed results, the transcriptomes of blastocysts obtained after injection of Igf2 mRNA in mouse parthenotes were analyzed. Sperm IGF2 mRNA negatively correlated with time of 2-cell stage (t2), t3, t4, t5, and time of expanded blastocyst (tEB), independently of maternal age, body mass index, anti-Müllerian hormone levels, and oocyte quality. An IGF2 mRNA index >4.9 predicted the ability of the embryos to reach the blastocyst stage on Day 5, with a sensitivity of 100% and a specificity of 71.6% (AUC 0.845; P < 0.001). In the animal study, transcriptome analysis demonstrated that 65 and 36 genes were, respectively, up- and down-regulated in the experimental group compared to the control group. These genes belong to pathways that regulate early embryo development, thus supporting the findings found in humans. This study has the potential to challenge the longstanding tenet that spermatozoa are simply vehicles carrying paternal DNA. Instead, it suggests that IGF2 mRNA in healthy spermatozoa provides critical support for early embryo development. Pre-ART sperm-carried IGF2 mRNA levels may be used as a marker to predict the chances of obtaining blastocysts to be transferred for infertile couples undergoing ART.

Inference of single-cell network using mutual information for scRNA-seq data analysis

BACKGROUND

With the advance in single-cell RNA sequencing (scRNA-seq) technology, deriving inherent biological system information from expression profiles at a single-cell resolution has become possible. It has been known that network modeling by estimating the associations between genes could better reveal dynamic changes in biological systems. However, accurately constructing a single-cell network (SCN) to capture the network architecture of each cell and further explore cell-to-cell heterogeneity remains challenging.

RESULTS

We introduce SINUM, a method for constructing the SIngle-cell Network Using Mutual information, which estimates mutual information between any two genes from scRNA-seq data to determine whether they are dependent or independent in a specific cell. Experiments on various scRNA-seq datasets with different cell numbers based on eight performance indexes (e.g., adjusted rand index and F-measure index) validated the accuracy and robustness of SINUM in cell type identification, superior to the state-of-the-art SCN inference method. Additionally, the SINUM SCNs exhibit high overlap with the human interactome and possess the scale-free property.

CONCLUSIONS

SINUM presents a view of biological systems at the network level to detect cell-type marker genes/gene pairs and investigate time-dependent changes in gene associations during embryo development. Codes for SINUM are freely available at https://github.com/SysMednet/SINUM .

Integrated ultrasensitive metabolomics and single-cell transcriptomics identify crucial regulators of sheep oocyte maturation and early embryo development in vitro

INTRODUCTION

Developmental competence of oocytes matured in vitro is limited due to a lack of complete understanding of metabolism and metabolic gene expression during oocyte maturation and embryo development. Conventional metabolic analysis requires a large number of samples and is not efficiently applicable in oocytes and early embryos, thereby posing challenges in identifying key metabolites and regulating their in vitro culture system.

OBJECTIVES

To enhance the developmental competence of sheep oocytes, this study aimed to identify and supplement essential metabolites that were deficient in the culture systems.

METHODS

The metabolic characteristics of oocytes and embryos were determined using ultrasensitive metabolomics analysis on trace samples and single-cell RNA-seq. By conducting integrated analyses of metabolites in cells (oocytes and embryos) and their developmental microenvironment (follicular fluid, oviductal fluid, and in vitro culture systems), we identified key missing metabolites in the in vitro culture systems. In order to assess the impact of these key missing metabolites on oocyte development competence, we performed in vitro culture experiments. Furthermore, omics analyses were employed to elucidate the underlying mechanisms.

RESULTS

Our findings demonstrated that betaine, carnitine and creatine were the key missing metabolites in vitro culture systems and supplementation of betaine and L-carnitine significantly improved the blastocyst formation rate (67.48% and 48.61%). Through in vitro culture experiments and omics analyses, we have discovered that L-carnitine had the potential to promote fatty acid oxidation, reduce lipid content and lipid peroxidation level, and regulate spindle morphological grade through fatty acid degradation pathway. Additionally, betaine may participate in methylation modification and osmotic pressure regulation, thereby potentially improving oocyte maturation and early embryo development in sheep.

CONCLUSION

Together, these analyses identified key metabolites that promote ovine oocyte maturation and early embryo development, while also providing a new viewpoint to improve clinical applications such as oocyte maturation or embryo culture.

Distinct dynamics of parental 5-hydroxymethylcytosine during human preimplantation development regulate early lineage gene expression

The conversion of DNA 5-methylcytosine (5mC) to 5-hydroxymethylcytosine (5hmC) by TET enzymes represents a significant epigenetic modification, yet its role in early human embryos remains largely unknown. Here we showed that the early human embryo inherited a significant amount of 5hmCs from an oocyte, which unexpectedly underwent de novo hydroxymethylation during its growth. Furthermore, the generation of 5hmC in the paternal genome after fertilization roughly followed the maternal pattern, which was linked to DNA methylation dynamics and regions of sustained methylation. The 5hmCs persisted until the eight-cell stage and exhibited high enrichment at OTX2 binding sites, whereas knockdown of OTX2 in human embryos compromised the expression of early lineage genes. Specifically, the depletion of 5hmC affected the activation of embryonic genes, which was further evaluated by ectopically expressing mouse Tet3 in human early embryos. These findings revealed distinct dynamics of 5hmC and unravelled its multifaceted functions in early human embryonic development.

FSCME: A Feature Selection Method Combining Copula Correlation and Maximal Information Coefficient by Entropy Weights

Feature selection is a critical component of data mining and has garnered significant attention in recent years. However, feature selection methods based on information entropy often introduce complex mutual information forms to measure features, leading to increased redundancy and potential errors. To address this issue, we propose FSCME, a feature selection method combining Copula correlation (Ccor) and the maximum information coefficient (MIC) by entropy weights. The FSCME takes into consideration the relevance between features and labels, as well as the redundancy among candidate features and selected features. Therefore, the FSCME utilizes Ccor to measure the redundancy between features, while also estimating the relevance between features and labels. Meanwhile, the FSCME employs MIC to enhance the credibility of the correlation between features and labels. Moreover, this study employs the Entropy Weight Method (EWM) to evaluate and assign weights to the Ccor and MIC. The experimental results demonstrate that FSCME yields a more effective feature subset for subsequent clustering processes, significantly improving the classification performance compared to the other six feature selection methods.

Transcriptome analysis reveals that defects in cell cycle regulation contribute to preimplantation embryo arrest

Patients with preimplantation embryo arrest (PREMBA) often experience assisted reproductive failure primarily due to the lack of transferable embryos, and the molecular mechanisms underlying PREMBA remain unclear. In our study, the embryos from five women with recurrent preimplantation embryo arrest and three women with tubal factor infertility were used for single-embryo transcriptome sequencing. Meanwhile, the transcriptomes of normal human preimplantation embryos obtained from GSE36552 were utilized to perform a comparative analysis with the transcriptomes of PREMBA embryos. Our results showed dysregulation of the cell cycle phase transition might be a potential pathogenic factor contributing to PREMBA. Through integrated analysis of the differentially expressed genes (DEGs) and weighted gene co-expression network analysis (WGCNA), we identified a number of hub genes using the protein-protein interaction network. The top 5 hub genes were as follows: CCNB2, BUB1B, CDC25A, CCNB3, and PLK3. The expression of hub genes was validated in PREMBA embryos and donated embryos using RT-qPCR. The knockdown of Ccnb2 in mouse zygotes led to an increase in embryo fragmentation, a rise in apoptosis, and a reduction in blastocyst formation. Furthermore, silencing the expression of CDC25A in HEK293T cells resulted in a decrease in cell proliferation and an increase in apoptosis, providing further support for our findings. Our findings could predict the development outcomes of preimplantation embryos and be used as potential therapeutic targets to prevent recurrent failures of IVF/ICSI attempts.

Mapping of long interspersed element-1 (L1) insertions by TIPseq provides information about sub chromosomal genetic variation in human embryos

PURPOSE

Retrotransposons play important roles during early development when they are transiently de-repressed during epigenetic reprogramming. Long interspersed element-1 (L1), the only autonomous retrotransposon in humans, comprises 17% of the human genome. We applied the Single Cell Transposon Insertion Profiling by Sequencing (scTIPseq) to characterize and map L1 insertions in human embryos.

METHODS

Sixteen cryopreserved, genetically tested, human blastocysts, were accessed from consenting couples undergoing IVF at NYU Langone Fertility Center. Additionally, four trios (father, mother, and embryos) were also evaluated. scTIPseq was applied to map L1 insertions in all samples, using L1 locations reported in the 1000 Genomes as controls.

RESULTS

Twenty-nine unknown and unique insertions were observed in the sixteen embryos. Most were intergenic; no insertions were located in exons or immediately upstream of genes. The location or number of unknown insertions did not differ between euploid and aneuploid embryos, suggesting they are not merely markers of aneuploidy. Rather, scTIPseq provides novel information about sub-chromosomal structural variation in human embryos. Trio analyses showed a parental origin of all L1 insertions in embryos.

CONCLUSION

Several studies have measured L1 expression at different stages of development in mice, but this study for the first time reports unknown insertions in human embryos that were inherited from one parent, confirming no de novo L1 insertions occurred in parental germline or during embryogenesis. Since one-third of euploid embryo transfers fail, future studies would be useful for understanding whether these sub-chromosomal genetic variants or de novo L1 insertions affect embryo developmental potential.

The pluripotency state of human embryonic stem cells derived from single blastomeres of eight-cell embryos

Human embryonic stem cells (hESCs) derived from blastocyst stage embryos present a primed state of pluripotency, whereas mouse ESCs (mESCs) display naïve pluripotency. Their unique characteristics make naïve hESCs more suitable for particular applications in biomedical research. This work aimed to derive hESCs from single blastomeres and determine their pluripotency state, which is currently unclear. We derived hESC lines from single blastomeres of 8-cell embryos and from whole blastocysts, and analysed several naïve pluripotency indicators, their transcriptomic profile and their trilineage differentiation potential. No significant differences were observed between blastomere-derived hESCs (bm-hESCs) and blastocyst-derived hESCs (bc-hESCs) for most naïve pluripotency indicators, including TFE3 localization, mitochondrial activity, and global DNA methylation and hydroxymethylation, nor for their trilineage differentiation potential. Nevertheless, bm-hESCs showed an increased single-cell clonogenicity and a higher expression of naïve pluripotency markers at early passages than bc-hESCs. Furthermore, RNA-seq revealed that bc-hESCs overexpressed a set of genes related to the post-implantational epiblast. Altogether, these results suggest that bm-hESCs, although displaying primed pluripotency, would be slightly closer to the naïve end of the pluripotency continuum than bc-hESCs.

Brain lncRNA-mRNA co-expression regulatory networks and alcohol use disorder

Prolonged alcohol consumption can disturb the expression of both coding and noncoding genes in the brain. These dysregulated genes may co-express in modules and interact within networks, consequently influencing the susceptibility to developing alcohol use disorder (AUD). In the present study, we performed an RNA-seq analysis of the expression of both long noncoding RNAs (lncRNAs) and messenger RNAs (mRNAs) in 192 postmortem tissue samples collected from eight brain regions (amygdala, caudate nucleus, cerebellum, hippocampus, nucleus accumbens, prefrontal cortex, putamen, and ventral tegmental area) of 12 AUD and 12 control subjects of European ancestry. Applying the limma-voom method, we detected a total of 57 lncRNAs and 51 mRNAs exhibiting significant differential expression (Padj < 0.05 and fold-change ≥2) across at least one of the eight brain regions investigated. Machine learning analysis further confirmed the potential of these top genes in predicting AUD. Through Weighted Gene Co-expression Network Analysis (WGCNA), we identified distinct lncRNA-mRNA co-expression modules associated with AUD in each of the eight brain regions. Additionally, lncRNA-mRNA co-expression networks were constructed for each brain region using Cytoscape to reveal gene regulatory interactions implicated in AUD. Hub genes within these networks were found to be enriched in several key KEGG pathways, including Axon Guidance, MAPK Signaling, p53 Signaling, Adherens Junction, and Neurodegeneration. Our results underscore the significance of networks involving AUD-associated lncRNAs and mRNAs in modulating neuroplasticity in response to alcohol exposure. Further elucidating these molecular mechanisms holds promise for the development of targeted therapeutic interventions for AUD.

Revisiting trophectoderm-inner cell mass lineage segregation in the mammalian preimplantation embryo

In the first days of life, cells of the mammalian embryo segregate into two distinct lineages, trophectoderm and inner cell mass. Unlike nonmammalian species, mammalian development does not proceed from predetermined factors in the oocyte. Rather, asymmetries arise de novo in the early embryo incorporating cues from cell position, contractility, polarity, and cell-cell contacts. Molecular heterogeneities, including transcripts and non-coding RNAs, have now been characterized as early as the 2-cell stage. However, it's debated whether these early heterogeneities bias cells toward one fate or the other or whether lineage identity arises stochastically at the 16-cell stage. This review summarizes what is known about early blastomere asymmetries and our understanding of lineage allocation in the context of historical models. Preimplantation development is reviewed coupled with what is known about changes in morphology, contractility, and transcription factor networks. The addition of single-cell atlases of human embryos has begun to reveal key differences between human and mouse, including the timing of events and core transcription factors. Furthermore, the recent generation of blastoid models will provide valuable tools to test and understand fate determinants. Lastly, new techniques are reviewed, which may better synthesize existing knowledge with emerging data sets and reconcile models with the regulative capacity unique to the mammalian embryo.