GenomeMUSter mouse genetic variation service enables multitrait, multipopulation data integration and analysis.

Hundreds of inbred mouse strains and intercross populations have been used to characterize the function of genetic variants that contribute to disease. Thousands of disease-relevant traits have been characterized in mice and made publicly available. New strains and populations including consomics, the collaborative cross, expanded BXD, and inbred wild-derived strains add to existing complex disease mouse models, mapping populations, and sensitized backgrounds for engineered mutations. The genome sequences of inbred strains, along with dense genotypes from others, enable integrated analysis of trait-variant associations across populations, but these analyses are hampered by the sparsity of genotypes available. Moreover, the data are not readily interoperable with other resources. To address these limitations, we created a uniformly dense variant resource by harmonizing multiple data sets. Missing genotypes were imputed using the Viterbi algorithm with a data-driven technique that incorporates local phylogenetic information, an approach that is extendable to other model organisms. The result is a web- and programmatically accessible data service called GenomeMUSter, comprising single-nucleotide variants covering 657 strains at 106.8 million segregating sites. Interoperation with phenotype databases, analytic tools, and other resources enable a wealth of applications, including multitrait, multipopulation meta-analysis. We show this in cross-species comparisons of type 2 diabetes and substance use disorder meta-analyses, leveraging mouse data to characterize the likely role of human variant effects in disease. Other applications include refinement of mapped loci and prioritization of strain backgrounds for disease modeling to further unlock extant mouse diversity for genetic and genomic studies in health and disease.

BCG vaccination stimulates integrated organ immunity by feedback of the adaptive immune response to imprint prolonged innate antiviral resistance.

Bacille Calmette-Guérin (BCG) vaccination can confer nonspecific protection against heterologous pathogens. However, the underlying mechanisms remain mysterious. We show that mice vaccinated intravenously with BCG exhibited reduced weight loss and/or improved viral clearance when challenged with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 B.1.351) or PR8 influenza. Protection was first evident between 14 and 21 d post-vaccination and lasted ∼3 months. Notably, BCG induced a biphasic innate response and robust antigen-specific type 1 helper T cell (TH1 cell) responses in the lungs. MyD88 signaling was essential for innate and TH1 cell responses, and protection against SARS-CoV-2. Depletion of CD4+ T cells or interferon (IFN)-γ activity before infection obliterated innate activation and protection. Single-cell and spatial transcriptomics revealed CD4-dependent expression of IFN-stimulated genes in lung myeloid and epithelial cells. Notably, BCG also induced protection against weight loss after mouse-adapted SARS-CoV-2 BA.5, SARS-CoV and SHC014 coronavirus infections. Thus, BCG elicits integrated organ immunity, where CD4+ T cells feed back on tissue myeloid and epithelial cells to imprint prolonged and broad innate antiviral resistance.

GenomeMUSter mouse genetic variation service enables multi-trait, multi-population data integration and analyses.

Hundreds of inbred laboratory mouse strains and intercross populations have been used to functionalize genetic variants that contribute to disease. Thousands of disease relevant traits have been characterized in mice and made publicly available. New strains and populations including the Collaborative Cross, expanded BXD and inbred wild-derived strains add to set of complex disease mouse models, genetic mapping resources and sensitized backgrounds against which to evaluate engineered mutations. The genome sequences of many inbred strains, along with dense genotypes from others could allow integrated analysis of trait - variant associations across populations, but these analyses are not feasible due to the sparsity of genotypes available. Moreover, the data are not readily interoperable with other resources. To address these limitations, we created a uniformly dense data resource by harmonizing multiple variant datasets. Missing genotypes were imputed using the Viterbi algorithm with a data-driven technique that incorporates local phylogenetic information, an approach that is extensible to other model organism species. The result is a web- and programmatically-accessible data service called GenomeMUSter ( https://muster.jax.org ), comprising allelic data covering 657 strains at 106.8M segregating sites. Interoperation with phenotype databases, analytic tools and other resources enable a wealth of applications including multi-trait, multi-population meta-analysis. We demonstrate this in a cross-species comparison of the meta-analysis of Type 2 Diabetes and of substance use disorders, resulting in the more specific characterization of the role of human variant effects in light of mouse phenotype data. Other applications include refinement of mapped loci and prioritization of strain backgrounds for disease modeling to further unlock extant mouse diversity for genetic and genomic studies in health and disease.

Targeting KDM2A Enhances T-cell Infiltration in NSD1-Deficient Head and Neck Squamous Cell Carcinoma.

In head and neck squamous cell carcinoma (HNSCC), a significant proportion of tumors have inactivating mutations in the histone methyltransferase NSD1. In these tumors, NSD1 inactivation is a driver of T-cell exclusion from the tumor microenvironment (TME). A better understanding of the NSD1-mediated mechanism regulating infiltration of T cells into the TME could help identify approaches to overcome immunosuppression. Here, we demonstrated that NSD1 inactivation results in lower levels of H3K36 dimethylation and higher levels of H3K27 trimethylation, the latter being a known repressive histone mark enriched on the promoters of key T-cell chemokines CXCL9 and CXCL10. HNSCC with NSD1 mutations had lower levels of these chemokines and lacked responses to PD-1 immune checkpoint blockade. Inhibition of KDM2A, the primary lysine demethylase that is selective for H3K36, reversed the altered histone marks induced by NSD1 loss and restored T-cell infiltration into the TME. Importantly, KDM2A suppression decreased growth of NSD1-deficient tumors in immunocompetent, but not in immunodeficient, mice. Together, these data indicate that KDM2A is an immunotherapeutic target for overcoming immune exclusion in HNSCC. SIGNIFICANCE: The altered epigenetic landscape of NSD1-deficient tumors confers sensitivity to inhibition of the histone-modifying enzyme KDM2A as an immunotherapeutic strategy to stimulate T-cell infiltration and suppress tumor growth.

PRPF8 controls alternative splicing of PIRH2 to modulate the p53 pathway and survival of human ESCs.

Human embryonic stem cells (hESCs) have great potential for developmental biology and regenerative medicine. However, extensive apoptosis often occurs when hESCs respond to various stresses or injuries. Understanding the molecular control and identifying new factors associated with hESC survival are fundamental to ensure the high quality of hESCs. In this study, we report that PRPF8, an RNA spliceosome component, is essential for hESC survival. PRPF8 knockdown (KD) induces p53 protein accumulation and activates the p53 pathway, leading to apoptosis in hESCs. Strikingly, silencing of p53 rescues PRPF8 KD-induced apoptosis, indicating that PRPF8 KD triggers hESC apoptosis through activating the p53 pathway. In search for the mechanism by which p53 pathway is activated by PRPF8 KD, we find that PRPF8 KD alters alternative splicing of many genes, including PIRH2 which encodes an E3 ubiquitin ligase of p53. PIRH2 has several isoforms such as PIRH2A, PIRH2B, and PIRH2C. Intriguingly, PRPF8 KD specifically increases the transcript level of the PIRH2B isoform, which lacks a RING domain and E3 ligase activity. Functionally, PIRH2B KD partially rescues the reduction in cell numbers and upregulation of P21 caused by PRPF8 KD in hESCs. The finding suggests that PRPF8 controls alternative splicing of PIRH2 to maintain the balance of p53 pathway activity and survival of hESCs. The PRPF8/PIRH2/p53 axis identified here provides new insights into how p53 pathway and hESC survival are precisely regulated at multiple layers, highlighting an important role of posttranscriptional machinery in supporting hESC survival.

Analysis of structural variation among inbred mouse strains.

BACKGROUND: 'Long read' sequencing methods have been used to identify previously uncharacterized structural variants that cause human genetic diseases. Therefore, we investigated whether long read sequencing could facilitate genetic analysis of murine models for human diseases. RESULTS: The genomes of six inbred strains (BTBR T + Itpr3tf/J, 129Sv1/J, C57BL/6/J, Balb/c/J, A/J, SJL/J) were analyzed using long read sequencing. Our results revealed that (i) Structural variants are very abundant within the genome of inbred strains (4.8 per gene) and (ii) that we cannot accurately infer whether structural variants are present using conventional short read genomic sequence data, even when nearby SNP alleles are known. The advantage of having a more complete map was demonstrated by analyzing the genomic sequence of BTBR mice. Based upon this analysis, knockin mice were generated and used to characterize a BTBR-unique 8-bp deletion within Draxin that contributes to the BTBR neuroanatomic abnormalities, which resemble human autism spectrum disorder. CONCLUSION: A more complete map of the pattern of genetic variation among inbred strains, which is produced by long read genomic sequencing of the genomes of additional inbred strains, could facilitate genetic discovery when murine models of human diseases are analyzed.

Innate immune cell activation causes lung fibrosis in a humanized model of long COVID.

COVID-19 remains a global pandemic of an unprecedented magnitude with millions of people now developing "COVID lung fibrosis." Single-cell transcriptomics of lungs of patients with long COVID revealed a unique immune signature demonstrating the upregulation of key proinflammatory and innate immune effector genes CD47, IL-6, and JUN. We modeled the transition to lung fibrosis after COVID and profiled the immune response with single-cell mass cytometry in JUN mice. These studies revealed that COVID mediated chronic immune activation reminiscent to long COVID in humans. It was characterized by increased CD47, IL-6, and phospho-JUN (pJUN) expression which correlated with disease severity and pathogenic fibroblast populations. When we subsequently treated a humanized COVID lung fibrosis model by combined blockade of inflammation and fibrosis, we not only ameliorated fibrosis but also restored innate immune equilibrium indicating possible implications for clinical management of COVID lung fibrosis in patients.

GSEApy: a comprehensive package for performing gene set enrichment analysis in Python.

MOTIVATION: Gene set enrichment analysis (GSEA) is a commonly used algorithm for characterizing gene expression changes. However, the currently available tools used to perform GSEA have a limited ability to analyze large datasets, which is particularly problematic for the analysis of single-cell data. To overcome this limitation, we developed a GSEA package in Python (GSEApy), which could efficiently analyze large single-cell datasets. RESULTS: We present a package (GSEApy) that performs GSEA in either the command line or Python environment. GSEApy uses a Rust implementation to enable it to calculate the same enrichment statistic as GSEA for a collection of pathways. The Rust implementation of GSEApy is 3-fold faster than the Numpy version of GSEApy (v0.10.8) and uses >4-fold less memory. GSEApy also provides an interface between Python and Enrichr web services, as well as for BioMart. The Enrichr application programming interface enables GSEApy to perform over-representation analysis for an input gene list. Furthermore, GSEApy consists of several tools, each designed to facilitate a particular type of enrichment analysis. AVAILABILITY AND IMPLEMENTATION: The new GSEApy with Rust extension is deposited in PyPI: https://pypi.org/project/gseapy/. The GSEApy source code is freely available at https://github.com/zqfang/GSEApy. Also, the documentation website is available at https://gseapy.rtfd.io/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

An automated multi-modal graph-based pipeline for mouse genetic discovery.

MOTIVATION: Our ability to identify causative genetic factors for mouse genetic models of human diseases and biomedical traits has been limited by the difficulties associated with identifying true causative factors, which are often obscured by the many false positive genetic associations produced by a GWAS. RESULTS: To accelerate the pace of genetic discovery, we developed a graph neural network (GNN)-based automated pipeline (GNNHap) that could rapidly analyze mouse genetic model data and identify high probability causal genetic factors for analyzed traits. After assessing the strength of allelic associations with the strain response pattern; this pipeline analyzes 29M published papers to assess candidate gene-phenotype relationships; and incorporates the information obtained from a protein-protein interaction network and protein sequence features into the analysis. The GNN model produces markedly improved results relative to that of a simple linear neural network. We demonstrate that GNNHap can identify novel causative genetic factors for murine models of diabetes/obesity and for cataract formation, which were validated by the phenotypes appearing in previously analyzed gene knockout mice. The diabetes/obesity results indicate how characterization of the underlying genetic architecture enables new therapies to be discovered and tested by applying 'precision medicine' principles to murine models. AVAILABILITY AND IMPLEMENTATION: The GNNHap source code is freely available at https://github.com/zqfang/gnnhap, and the new version of the HBCGM program is available at https://github.com/zqfang/haplomap. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A human multi-lineage hepatic organoid model for liver fibrosis.

To investigate the pathogenesis of a congenital form of hepatic fibrosis, human hepatic organoids were engineered to express the most common causative mutation for Autosomal Recessive Polycystic Kidney Disease (ARPKD). Here we show that these hepatic organoids develop the key features of ARPKD liver pathology (abnormal bile ducts and fibrosis) in only 21 days. The ARPKD mutation increases collagen abundance and thick collagen fiber production in hepatic organoids, which mirrors ARPKD liver tissue pathology. Transcriptomic and other analyses indicate that the ARPKD mutation generates cholangiocytes with increased TGFß pathway activation, which are actively involved stimulating myofibroblasts to form collagen fibers. There is also an expansion of collagen-producing myofibroblasts with markedly increased PDGFRB protein expression and an activated STAT3 signaling pathway. Moreover, the transcriptome of ARPKD organoid myofibroblasts resemble those present in commonly occurring forms of liver fibrosis. PDGFRB pathway involvement was confirmed by the anti-fibrotic effect observed when ARPKD organoids were treated with PDGFRB inhibitors. Besides providing insight into the pathogenesis of congenital (and possibly acquired) forms of liver fibrosis, ARPKD organoids could also be used to test the anti-fibrotic efficacy of potential anti-fibrotic therapies.

The Effect of Population Structure on Murine Genome-Wide Association Studies.

The ability to use genome-wide association studies (GWAS) for genetic discovery depends upon our ability to distinguish true causative from false positive association signals. Population structure (PS) has been shown to cause false positive signals in GWAS. PS correction is routinely used for analysis of human GWAS results, and it has been assumed that it also should be utilized for murine GWAS using inbred strains. Nevertheless, there are fundamental differences between murine and human GWAS, and the impact of PS on murine GWAS results has not been carefully investigated. To assess the impact of PS on murine GWAS, we examined 8223 datasets that characterized biomedical responses in panels of inbred mouse strains. Rather than treat PS as a confounding variable, we examined it as a response variable. Surprisingly, we found that PS had a minimal impact on datasets measuring responses in ≤20 strains; and had surprisingly little impact on most datasets characterizing 21 - 40 inbred strains. Moreover, we show that true positive association signals arising from haplotype blocks, SNPs or indels, which were experimentally demonstrated to be causative for trait differences, would be rejected if PS correction were applied to them. Our results indicate because of the special conditions created by GWAS (the use of inbred strains, small sample sizes) PS assessment results should be carefully evaluated in conjunction with other criteria, when murine GWAS results are evaluated.

Calcineurin A gamma and NFATc3/SRPX2 axis contribute to human embryonic stem cell differentiation.

Our understanding of signaling pathways regulating the cell fate of human embryonic stem cells (hESCs) is limited. Calcineurin-NFAT signaling is associated with a wide range of biological processes and diseases. However, its role in controlling hESC fate remains unclear. Here, we report that calcineurin A gamma and the NFATc3/SRPX2 axis control the expression of lineage and epithelial-mesenchymal transition (EMT) markers in hESCs. Knockdown of PPP3CC, the gene encoding calcineurin A gamma, or NFATC3, downregulates certain markers both at the self-renewal state and during differentiation of hESCs. Furthermore, NFATc3 interacts with c-JUN and regulates the expression of SRPX2, the gene encoding a secreted glycoprotein known as a ligand of uPAR. We show that SRPX2 is a downstream target of NFATc3. Both SRPX2 and uPAR participate in controlling expression of lineage and EMT markers. Importantly, SRPX2 knockdown diminishes the upregulation of multiple lineage and EMT markers induced by co-overexpression of NFATc3 and c-JUN in hESCs. Together, this study uncovers a previously unknown role of calcineurin A gamma and the NFATc3/SRPX2 axis in modulating the fate determination of hESCs.

SOX1 Is Required for the Specification of Rostral Hindbrain Neural Progenitor Cells from Human Embryonic Stem Cells.

Region-specific neural progenitor cells (NPCs) can be generated from human embryonic stem cells (hESCs) by modulating signaling pathways. However, how intrinsic transcriptional factors contribute to the neural regionalization is not well characterized. Here, we generate region-specific NPCs from hESCs and find that SOX1 is highly expressed in NPCs with the rostral hindbrain identity. Moreover, we find that OTX2 inhibits SOX1 expression, displaying exclusive expression between the two factors. Furthermore, SOX1 knockout (KO) leads to the upregulation of midbrain genes and downregulation of rostral hindbrain genes, indicating that SOX1 is required for specification of rostral hindbrain NPCs. Our SOX1 chromatin immunoprecipitation sequencing analysis reveals that SOX1 binds to the distal region of GBX2 to activate its expression. Overexpression of GBX2 largely abrogates SOX1-KO-induced aberrant gene expression. Taken together, this study uncovers previously unappreciated role of SOX1 in early neural regionalization and provides new information for the precise control of the OTX2/GBX2 interface.

CDK11 safeguards the identity of human embryonic stem cells via fine-tuning signaling pathways.

Signaling pathways transmit extracellular cues into cells and regulate transcriptome and epigenome to maintain or change the cell identity. Protein kinases and phosphatases are critical for signaling transduction and regulation. Here, we report that CDK11, a member of the CDK family, is required for the maintenance of human embryonic stem cell (hESC) self-renewal. Our results show that, among the three main isoforms of CDK11, CDK11p46 is the main isoform safeguarding the hESC identity. Mechanistically, CDK11 constrains two important mitogen-activated protein kinase (MAPK) signaling pathways (JNK and p38 signaling) through modulating the activity of protein phosphatase 1. Furthermore, CDK11 knockdown activates transforming growth factor ß (TGF-ß)/SMAD2/3 signaling and upregulates certain nonneural differentiation-associated genes. Taken together, this study uncovers a kinase required for hESC self-renewal through fine-tuning MAPK and TGF-ß signaling at appropriate levels. The kinase-phosphatase axis reported here may shed new light on the molecular mechanism sustaining the identity of hESCs.

SOX21 Ensures Rostral Forebrain Identity by Suppression of WNT8B during Neural Regionalization of Human Embryonic Stem Cells.

The generation of brain region-specific progenitors from human embryonic stem cells (hESCs) is critical for their application. However, transcriptional regulation of neural regionalization in humans is poorly understood. Here, we applied a rostrocaudal patterning system from hESCs to dissect global transcriptional networks controlling early neural regionalization. We found that SOX21 is required for rostral forebrain fate specification. SOX21 knockout led to activation of Wnt signaling, resulting in caudalization of regional identity of rostral forebrain neural progenitor cells. Moreover, we identified WNT8B as a SOX21 direct target. Deletion of WNT8B or inhibition of Wnt signaling in SOX21 knockout neural progenitor cells restored rostral forebrain identity. Furthermore, SOX21 interacted with ß-catenin, interfering with the binding of TCF4/ß-catenin complex to the WNT8B enhancer. Collectively, these results unveil the unknown role of SOX21 and shed light on how a transcriptional factor modulates early neural regionalization through crosstalk with a key component of Wnt signaling.

How Does Financial Development Affect Reductions in Carbon Emissions in High-Energy Industries?-A Perspective on Technological Progress.

Climate change has made countries around the world realize the importance of reducing carbon emissions. Reductions in carbon emissions needs the support of policy, technology, and financial capital. The single/double/three-threshold model is used here with data from China to study the different impact of financial development in carbon emissions in high-energy industries when the threshold variables are in different intervals. The results show that when loan size is the core explanatory variable, and research and development (R and D) expenditure and energy structure are the threshold variables, the loan size variable has a significant effect on emission reductions in high-energy industries, and this effect is strengthened with increases in R and D expenditure and decreases in the proportion of energy from coal. Taking energy intensity as the threshold variable, the relationship between loan size and carbon dioxide emissions is V-shaped. With economic structure as the threshold variable, loan size has a significant effect on emissions reduction when the proportion of industrial added value in high-energy industries is low. When using foreign investment as the core explanatory variable, R and D expenditure, energy consumption intensity, and industrial structure are threshold variables. The impact of foreign investment on carbon dioxide emissions is negative, but when the threshold variable is within different intervals, this negative impact differs. With stock market value as the core explanatory variable, and R and D expenditure and energy structure as the threshold variables, the stock market value can promote reductions in carbon emissions, but when R and D expenditure and the proportion of coal consumption is high, stock market value has no significant effect on emissions reduction. When energy consumption intensity is the threshold variable, the relationship between stock market value and carbon dioxide emissions is V-shaped.

Stk40 deletion elevates c-JUN protein level and impairs mesoderm differentiation.

Mesoderm development is a finely tuned process initiated by the differentiation of pluripotent epiblast cells. Serine/threonine kinase 40 (STK40) controls the development of several mesoderm-derived cell types, its overexpression induces differentiation of mouse embryonic stem cells (mESCs) toward the extraembryonic endoderm, and Stk40 knockout (KO) results in multiple organ failure and is lethal at the perinatal stage in mice. However, molecular mechanisms underlying the physiological functions of STK40 in mesoderm differentiation remain elusive. Here, we report that Stk40 ablation impairs mesoderm differentiation both in vitro and in vivo Mechanistically, STK40 interacts with both the E3 ubiquitin ligase mammalian constitutive photomorphogenesis protein 1 (COP1) and the transcriptional regulator proto-oncogene c-Jun (c-JUN), promoting c-JUN protein degradation. Consequently, Stk40 knockout leads to c-JUN protein accumulation, which, in turn, apparently suppresses WNT signaling activity and impairs the mesoderm differentiation process. Overall, this study reveals that STK40, together with COP1, represents a previously unknown regulatory axis that modulates the c-JUN protein level within an appropriate range during mesoderm differentiation from mESCs. Our findings provide critical insights into the molecular mechanisms regulating the c-JUN protein level and may have potential implications for managing cellular disorders arising from c-JUN dysfunction.

Spatial Effects of Technological Progress and Financial Support on China's Provincial Carbon Emissions.

The spatial autocorrelation analysis method was applied to panel data from the provinces of China (including autonomous regions and municipalities directly under the central government) for the period 2003 to 2016 in order to construct a spatial Durbin model of technological progress and financial support in relation to reductions in carbon emissions. The results show that China's carbon intensity presents significant spatial spillover effects under different spatial weights, which indicates that the carbon intensity of a province is influenced not only by its own characteristics, but also by the carbon emission behaviors of geographically adjacent and economically similar provinces and regions. Financial structure, financial scale, and financial efficiency all have significant effects on carbon intensity within a province, while financial structure is also linked to carbon intensity in other regions, but financial scale has no significant spillover effect on carbon intensity in space. Areas with high financial efficiency can reduce their own carbon intensity as well as that of surrounding areas. The inter-regional spillover effect of technological progress on carbon intensity is stronger than the spillover effect, but there is a time lag.

Transcription coactivator Cited1 acts as an inducer of trophoblast-like state from mouse embryonic stem cells through the activation of BMP signaling.

Trophoblast lineages, precursors of the placenta, are essential for post-implantation embryo survival. However, the regulatory network of trophoblast development remains incompletely understood. Here, we report that Cited1, a transcription coactivator, is a robust inducer for trophoblast-like state from mouse embryonic stem cells (ESCs). Depletion of Cited1 in ESCs compromises the trophoblast lineage specification induced by BMP signaling. In contrast, overexpression of Cited1 in ESCs induces a trophoblast-like state with elevated expression of trophoblast marker genes in vitro and generation of trophoblastic tumors in vivo. Furthermore, global transcriptome profile analysis indicates that ectopic Cited1 activates a trophoblast-like transcriptional program in ESCs. Mechanistically, Cited1 interacts with Bmpr2 and Smad4 to activate the Cited1-Bmpr2-Smad1/5/8 axis in the cytoplasm and Cited1-Smad4-p300 complexes in the nucleus, respectively. Collectively, our results show that Cited1 plays an important role in regulating trophoblast lineage specification through activating the BMP signaling pathway.

Single-cell analysis reveals lineage segregation in early post-implantation mouse embryos.

The mammalian post-implantation embryo has been extensively investigated at the tissue level. However, to unravel the molecular basis for the cell-fate plasticity and determination, it is essential to study the characteristics of individual cells. In particular, the individual definitive endoderm (DE) cells have not been characterized in vivo Here, we report gene expression patterns in single cells freshly isolated from mouse embryos on days 5.5 and 6.5. Initial transcriptome data from 124 single cells yielded signature genes for the epiblast, visceral endoderm, and extra-embryonic ectoderm and revealed a unique distribution pattern of fibroblast growth factor (FGF) ligands and receptors. Further analysis indicated that early-stage epiblast cells do not segregate into lineages of the major germ layers. Instead, some cells began to diverge from epiblast cells, displaying molecular features of the premesendoderm by expressing higher levels of mesendoderm markers and lower levels of Sox3 transcripts. Analysis of single-cell high-throughput quantitative RT-PCR data from 441 cells identified a late stage of the day 6.5 embryo in which mesoderm and DE cells emerge, with many of them coexpressing Oct4 and Gata6 Analysis of single-cell RNA-sequence data from 112 cells of the late-stage day 6.5 embryos revealed differentially expressed signaling genes and networks of transcription factors that might underlie the segregation of the mesoderm and DE lineages. Moreover, we discovered a subpopulation of mesoderm cells that possess molecular features of the extraembryonic mesoderm. This study provides fundamental insight into the molecular basis for lineage segregation in post-implantation mouse embryos.