Maternal factor Trim75 contributes to zygotic genome activation program in mouse early embryos.

BACKGROUND: Zygotic genome activation (ZGA) is an important event in the early embryo development, and human embryo developmental arrest has been highly correlated with ZGA failure in clinical studies. Although a few studies have linked maternal factors to mammalian ZGA, more studies are needed to fully elucidate the maternal factors that are involved in ZGA. METHODS AND RESULTS: In this study, we utilized published single-cell RNA sequencing data from a Dux-mediated mouse embryonic stem cell to induce a 2-cell-like transition state and selected potential drivers for the transition according to an RNA velocity analysis. CONCLUSIONS: An overlap of potential candidate markers of 2-cell-like-cells identified in this research with markers generated by various data sets suggests that Trim75 is a potential driver of minor ZGA and may recruit EP300 and establish H3K27ac in the gene body of minor ZGA genes, thereby contributing to mammalian preimplantation embryo development.

Lactate regulates major zygotic genome activation by H3K18 lactylation in mammals.

Lactate is present at a high level in the microenvironment of mammalian preimplantation embryos in vivo and in vitro. However, its role in preimplantation development is unclear. Here, we report that lactate is highly enriched in the nuclei of early embryos when major zygotic genome activation (ZGA) occurs in humans and mice. The inhibition of its production and uptake results in developmental arrest at the 2-cell stage, major ZGA failure, and loss of lactate-derived H3K18lac, which could be rescued by the addition of Lac-CoA and recapitulated by overexpression of H3K18R mutation. By profiling the landscape of H3K18lac during mouse preimplantation development, we show that H3K18lac is enriched on the promoter regions of most major ZGA genes and correlates with their expressions. In humans, H3K18lac is also enriched in ZGA markers and temporally concomitant with their expressions. Taken together, we profile the landscapes of H3K18lac in mouse and human preimplantation embryos, and demonstrate the important role for H3K18lac in major ZGA, showing that a conserved metabolic mechanism underlies preimplantation development of mammalian embryos.

Network characterization linc1393 in the maintenance of pluripotency provides the principles for lncRNA targets prediction.

Long non-coding RNAs (lncRNAs) have been implicated in diverse biological processes. However, the functional mechanisms have not yet been fully explored. Characterizing the interactions of lncRNAs with chromatin is central to determining their functions but, due to precise and efficient approaches lacking, our understanding of their functional mechanisms has progressed slowly. In this study, we demonstrate that a nuclear lncRNA linc1393 maintains mouse ESC pluripotency by recruiting SET1A near its binding sites, to establish H3K4me3 status and activate the expression of specific pluripotency-related genes. Moreover, we characterized the principles of lncRNA-chromatin interaction and transcriptional regulation. Accordingly, we developed a computational framework based on the XGBoost model, LncTargeter, to predict the targets of a given lncRNA, and validated its reliability in various cellular contexts. Together, these findings elucidate the roles and mechanisms of lncRNA on pluripotency maintenance, and provide a promising tool for predicting the regulatory networks of lncRNAs.

Deep annotation of long noncoding RNAs by assembling RNA-seq and small RNA-seq data.

Long noncoding RNAs (lncRNAs) are increasingly being recognized as modulators in various biological processes. However, due to their low expression, their systematic characterization is difficult to determine. Here, we performed transcript annotation by a newly developed computational pipeline, termed RNA-seq and small RNA-seq combined strategy (RSCS), in a wide variety of cellular contexts. Thousands of high-confidence potential novel transcripts were identified by the RSCS, and the reliability of the transcriptome was verified by analysis of transcript structure, base composition, and sequence complexity. Evidenced by the length comparison, the frequency of the core promoter and the polyadenylation signal motifs, and the locations of transcription start and end sites, the transcripts appear to be full length. Furthermore, taking advantage of our strategy, we identified a large number of endogenous retrovirus-associated lncRNAs, and a novel endogenous retrovirus-lncRNA that was functionally involved in control of Yap1 expression and essential for early embryogenesis was identified. In summary, the RSCS can generate a more complete and precise transcriptome, and our findings greatly expanded the transcriptome annotation for the mammalian community.

Metabolic control of histone acetylation for precise and timely regulation of minor ZGA in early mammalian embryos.

Metabolism feeds into the regulation of epigenetics via metabolic enzymes and metabolites. However, metabolic features, and their impact on epigenetic remodeling during mammalian pre-implantation development, remain poorly understood. In this study, we established the metabolic landscape of mouse pre-implantation embryos from zygote to blastocyst, and quantified some absolute carbohydrate metabolites. We integrated these data with transcriptomic and proteomic data, and discovered the metabolic characteristics of the development process, including the activation of methionine cycle from 8-cell embryo to blastocyst, high glutaminolysis metabolism at blastocyst stage, enhanced TCA cycle activity from the 8-cell embryo stage, and active glycolysis in the blastocyst. We further demonstrated that oxidized nicotinamide adenine dinucleotide (NAD+) synthesis is indispensable for mouse pre-implantation development. Mechanistically, in part, NAD+ is required for the exit of minor zygotic gene activation (ZGA) by cooperating with SIRT1 to remove zygotic H3K27ac. In human, NAD+ supplement can promote the removal of zygotic H3K27ac and benefit pre-implantation development. Our findings demonstrate that precise and timely regulation of minor ZGA is controlled by metabolic dynamics, and enhance our understanding of the metabolism of mammalian early embryos.

Argonaute 2 is a key regulator of maternal mRNA degradation in mouse early embryos.

In mammalian early embryos, the transition from maternal to embryonic control of gene expression requires timely degradation of a subset of maternal mRNAs (MRD). Recently, zygotic genome activation (ZGA)-dependent MRD has been characterized in mouse 2-cell embryo. However, in early embryos, the dynamics of MRD is still poorly understood, and the maternal factor-mediated MRD before and along with ZGA has not been investigated. Argonaute 2 (Ago2) is highly expressed in mouse oocyte and early embryos. In this study, we showed that Ago2-dependent degradation involving RNA interference (RNAi) and RNA activation (RNAa) pathways contributes to the decay of over half of the maternal mRNAs in mouse early embryos. We demonstrated that AGO2 guided by endogenous small interfering RNAs (endosiRNAs), generated from double-stranded RNAs (dsRNAs) formed by maternal mRNAs with their complementary long noncoding RNAs (CMR-lncRNAs), could target maternal mRNAs and cooperate with P-bodies to promote MRD. In addition, we also showed that AGO2 may interact with small activating RNAs (saRNAs) to activate Yap1 and Tead4, triggering ZGA-dependent MRD. Thus, Ago2-dependent degradation is required for timely elimination of subgroups of maternal mRNAs and facilitates the transition between developmental states.

Time series prediction with improved neuro-endocrine model.

The paper is focused on improving the performance of neuro-endocrine models with considering the interaction of glands. Comparing to conventional neuro-endocrine models, the concentration of hormone of one gland is modulated by those of others, and the weights of cells are modulated by the improved endocrine system. The interacted equation among all glands is designed and the parameters of them are chosen with theory analysis. Because all the parameters of the model are constants when the system reaches the equilibrium state, particle swarm optimization algorithm is utilized to search the optimal parameters of the model. The theory analysis indicates that the performance of neuro-endocrine model is better than or at least equal to that of corresponding artificial neural network. To indicate the effectiveness of the proposed model, some time series from different research fields, which are used in some literatures, are tested with the proposed model, the results indicate that the proposed model has some good performance.