Dissecting embryonic and extraembryonic lineage crosstalk with stem cell co-culture.

Embryogenesis necessitates harmonious coordination between embryonic and extraembryonic tissues. Although stem cells of both embryonic and extraembryonic origins have been generated, they are grown in different culture conditions. In this study, utilizing a unified culture condition that activates the FGF, TGF-ß, and WNT pathways, we have successfully derived embryonic stem cells (FTW-ESCs), extraembryonic endoderm stem cells (FTW-XENs), and trophoblast stem cells (FTW-TSCs) from the three foundational tissues of mouse and cynomolgus monkey (Macaca fascicularis) blastocysts. This approach facilitates the co-culture of embryonic and extraembryonic stem cells, revealing a growth inhibition effect exerted by extraembryonic endoderm cells on pluripotent cells, partially through extracellular matrix signaling. Additionally, our cross-species analysis identified both shared and unique transcription factors and pathways regulating FTW-XENs. The embryonic and extraembryonic stem cell co-culture strategy offers promising avenues for developing more faithful embryo models and devising more developmentally pertinent differentiation protocols.

Distinct developmental pathways generate functionally distinct populations of natural killer cells.

Natural killer (NK) cells function by eliminating virus-infected or tumor cells. Here we identified an NK-lineage-biased progenitor population, referred to as early NK progenitors (ENKPs), which developed into NK cells independently of common precursors for innate lymphoid cells (ILCPs). ENKP-derived NK cells (ENKP_NK cells) and ILCP-derived NK cells (ILCP_NK cells) were transcriptionally different. We devised combinations of surface markers that identified highly enriched ENKP_NK and ILCP_NK cell populations in wild-type mice. Furthermore, Ly49H+ NK cells that responded to mouse cytomegalovirus infection primarily developed from ENKPs, whereas ILCP_NK cells were better IFNγ producers after infection with Salmonella and herpes simplex virus. Human CD56dim and CD56bright NK cells were transcriptionally similar to ENKP_NK cells and ILCP_NK cells, respectively. Our findings establish the existence of two pathways of NK cell development that generate functionally distinct NK cell subsets in mice and further suggest these pathways may be conserved in humans.

High-dimensional single-cell analysis of human natural killer cell heterogeneity.

Natural killer (NK) cells are innate lymphoid cells (ILCs) contributing to immune responses to microbes and tumors. Historically, their classification hinged on a limited array of surface protein markers. Here, we used single-cell RNA sequencing (scRNA-seq) and cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) to dissect the heterogeneity of NK cells. We identified three prominent NK cell subsets in healthy human blood: NK1, NK2 and NK3, further differentiated into six distinct subgroups. Our findings delineate the molecular characteristics, key transcription factors, biological functions, metabolic traits and cytokine responses of each subgroup. These data also suggest two separate ontogenetic origins for NK cells, leading to divergent transcriptional trajectories. Furthermore, we analyzed the distribution of NK cell subsets in the lung, tonsils and intraepithelial lymphocytes isolated from healthy individuals and in 22 tumor types. This standardized terminology aims at fostering clarity and consistency in future research, thereby improving cross-study comparisons.

Transcription factor Tox2 is required for metabolic adaptation and tissue residency of ILC3 in the gut.

Group 3 innate lymphoid cells (ILC3) are the major subset of gut-resident ILC with essential roles in infections and tissue repair, but how they adapt to the gut environment to maintain tissue residency is unclear. We report that Tox2 is critical for gut ILC3 maintenance and function. Gut ILC3 highly expressed Tox2, and depletion of Tox2 markedly decreased ILC3 in gut but not at central sites, resulting in defective control of Citrobacter rodentium infection. Single-cell transcriptional profiling revealed decreased expression of Hexokinase-2 in Tox2-deficient gut ILC3. Consistent with the requirement for hexokinases in glycolysis, Tox2-/- ILC3 displayed decreased ability to utilize glycolysis for protein translation. Ectopic expression of Hexokinase-2 rescued Tox2-/- gut ILC3 defects. Hypoxia and interleukin (IL)-17A each induced Tox2 expression in ILC3, suggesting a mechanism by which ILC3 adjusts to fluctuating environments by programming glycolytic metabolism. Our results reveal the requirement for Tox2 to support the metabolic adaptation of ILC3 within the gastrointestinal tract.

Transcription factors TCF-1 and GATA3 are key factors for the epigenetic priming of early innate lymphoid progenitors toward distinct cell fates.

The differentiation of innate lymphoid cells (ILCs) from hematopoietic stem cells needs to go through several multipotent progenitor stages. However, it remains unclear whether the fates of multipotent progenitors are predefined by epigenetic states. Here, we report the identification of distinct accessible chromatin regions in all lymphoid progenitors (ALPs), EILPs, and ILC precursors (ILCPs). Single-cell MNase-seq analyses revealed that EILPs contained distinct subpopulations epigenetically primed toward either dendritic cell lineages or ILC lineages. We found that TCF-1 and GATA3 co-bound to the lineage-defining sites for ILCs (LDS-Is), whereas PU.1 binding was enriched in the LDSs for alternative dendritic cells (LDS-As). TCF-1 and GATA3 were indispensable for the epigenetic priming of LDSs at the EILP stage. Our results suggest that the multipotency of progenitor cells is defined by the existence of a heterogeneous population of cells epigenetically primed for distinct downstream lineages, which are regulated by key transcription factors.

MLL4 prepares the enhancer landscape for Foxp3 induction via chromatin looping.

MLL4 is an essential subunit of the histone H3 Lys4 (H3K4)-methylation complexes. We found that MLL4 deficiency compromised the development of regulatory T cells (Treg cells) and resulted in a substantial decrease in monomethylated H3K4 (H3K4me1) and chromatin interaction at putative gene enhancers, a considerable portion of which were not direct targets of MLL4 but were enhancers that interacted with MLL4-bound sites. The decrease in H3K4me1 and chromatin interaction at the enhancers not bound by MLL4 correlated with MLL4 binding at distant interacting regions. Deletion of an upstream MLL4-binding site diminished the abundance of H3K4me1 at the regulatory elements of the gene encoding the transcription factor Foxp3 that were looped to the MLL4-binding site and compromised both the thymic differentiation and the inducible differentiation of Treg cells. We found that MLL4 catalyzed methylation of H3K4 at distant unbound enhancers via chromatin looping, which identifies a previously unknown mechanism for regulating the T cell enhancer landscape and affecting Treg cell differentiation.

Polygenic scoring accuracy varies across the genetic ancestry continuum.

Polygenic scores (PGSs) have limited portability across different groupings of individuals (for example, by genetic ancestries and/or social determinants of health), preventing their equitable use1-3. PGS portability has typically been assessed using a single aggregate population-level statistic (for example, R2)4, ignoring inter-individual variation within the population. Here, using a large and diverse Los Angeles biobank5 (ATLAS, n = 36,778) along with the UK Biobank6 (UKBB, n = 487,409), we show that PGS accuracy decreases individual-to-individual along the continuum of genetic ancestries7 in all considered populations, even within traditionally labelled 'homogeneous' genetic ancestries. The decreasing trend is well captured by a continuous measure of genetic distance (GD) from the PGS training data: Pearson correlation of -0.95 between GD and PGS accuracy averaged across 84 traits. When applying PGS models trained on individuals labelled as white British in the UKBB to individuals with European ancestries in ATLAS, individuals in the furthest GD decile have 14% lower accuracy relative to the closest decile; notably, the closest GD decile of individuals with Hispanic Latino American ancestries show similar PGS performance to the furthest GD decile of individuals with European ancestries. GD is significantly correlated with PGS estimates themselves for 82 of 84 traits, further emphasizing the importance of incorporating the continuum of genetic ancestries in PGS interpretation. Our results highlight the need to move away from discrete genetic ancestry clusters towards the continuum of genetic ancestries when considering PGSs.

Apoptosis in response to microbial infection induces autoreactive TH17 cells.

Microbial infections often precede the onset of autoimmunity. How infections trigger autoimmunity remains poorly understood. We investigated the possibility that infection might create conditions that allow the stimulatory presentation of self peptides themselves and that this might suffice to elicit autoreactive T cell responses that lead to autoimmunity. Self-reactive CD4(+) T cells are major drivers of autoimmune disease, but their activation is normally prevented through regulatory mechanisms that limit the immunostimulatory presentation of self antigens. Here we found that the apoptosis of infected host cells enabled the presentation of self antigens by major histocompatibility complex class II molecules in an inflammatory context. This was sufficient for the generation of an autoreactive TH17 subset of helper T cells, prominently associated with autoimmune disease. Once induced, the self-reactive TH17 cells promoted auto-inflammation and autoantibody generation. Our findings have implications for how infections precipitate autoimmunity.

The γδ IEL effector API5 masks genetic susceptibility to Paneth cell death.

Loss of Paneth cells and their antimicrobial granules compromises the intestinal epithelial barrier and is associated with Crohn's disease, a major type of inflammatory bowel disease1-7. Non-classical lymphoid cells, broadly referred to as intraepithelial lymphocytes (IELs), intercalate the intestinal epithelium8,9. This anatomical position has implicated them as first-line defenders in resistance to infections, but their role in inflammatory disease pathogenesis requires clarification. The identification of mediators that coordinate crosstalk between specific IEL and epithelial subsets could provide insight into intestinal barrier mechanisms in health and disease. Here we show that the subset of IELs that express γ and δ T cell receptor subunits (γδ IELs) promotes the viability of Paneth cells deficient in the Crohn's disease susceptibility gene ATG16L1. Using an ex vivo lymphocyte-epithelium co-culture system, we identified apoptosis inhibitor 5 (API5) as a Paneth cell-protective factor secreted by γδ IELs. In the Atg16l1-mutant mouse model, viral infection induced a loss of Paneth cells and enhanced susceptibility to intestinal injury by inhibiting the secretion of API5 from γδ IELs. Therapeutic administration of recombinant API5 protected Paneth cells in vivo in mice and ex vivo in human organoids with the ATG16L1 risk allele. Thus, we identify API5 as a protective γδ IEL effector that masks genetic susceptibility to Paneth cell death.

Multi-ancestry polygenic risk scores for venous thromboembolism.

Venous thromboembolism (VTE) is a significant contributor to morbidity and mortality, with large disparities in incidence rates between Black and White Americans. Polygenic risk scores (PRSs) limited to variants discovered in genome-wide association studies in European-ancestry samples can identify European-ancestry individuals at high risk of VTE. However, there is limited evidence on whether high-dimensional PRS constructed using more sophisticated methods and more diverse training data can enhance the predictive ability and their utility across diverse populations. We developed PRSs for VTE using summary statistics from the International Network against Venous Thrombosis (INVENT) consortium genome-wide association studies meta-analyses of European- (71 771 cases and 1 059 740 controls) and African-ancestry samples (7482 cases and 129 975 controls). We used LDpred2 and PRS-CSx to construct ancestry-specific and multi-ancestry PRSs and evaluated their performance in an independent European- (6781 cases and 103 016 controls) and African-ancestry sample (1385 cases and 12 569 controls). Multi-ancestry PRSs with weights tuned in European-ancestry samples slightly outperformed ancestry-specific PRSs in European-ancestry test samples (e.g. the area under the receiver operating curve [AUC] was 0.609 for PRS-CSx_combinedEUR and 0.608 for PRS-CSxEUR [P = 0.00029]). Multi-ancestry PRSs with weights tuned in African-ancestry samples also outperformed ancestry-specific PRSs in African-ancestry test samples (PRS-CSxAFR: AUC = 0.58, PRS-CSx_combined AFR: AUC = 0.59), although this difference was not statistically significant (P = 0.34). The highest fifth percentile of the best-performing PRS was associated with 1.9-fold and 1.68-fold increased risk for VTE among European- and African-ancestry subjects, respectively, relative to those in the middle stratum. These findings suggest that the multi-ancestry PRS might be used to improve performance across diverse populations to identify individuals at highest risk for VTE.

Genotype error due to low-coverage sequencing induces uncertainty in polygenic scoring.

Polygenic scores (PGSs) have emerged as a standard approach to predict phenotypes from genotype data in a wide array of applications from socio-genomics to personalized medicine. Traditional PGSs assume genotype data to be error-free, ignoring possible errors and uncertainties introduced from genotyping, sequencing, and/or imputation. In this work, we investigate the effects of genotyping error due to low coverage sequencing on PGS estimation. We leverage SNP array and low-coverage whole-genome sequencing data (lcWGS, median coverage 0.04×) of 802 individuals from the Dana-Farber PROFILE cohort to show that PGS error correlates with sequencing depth (p = 1.2 × 10-7). We develop a probabilistic approach that incorporates genotype error in PGS estimation to produce well-calibrated PGS credible intervals and show that the probabilistic approach increases classification accuracy by up to 6% as compared to traditional PGSs that ignore genotyping error. Finally, we use simulations to explore the combined effect of genotyping and effect size errors and their implication on PGS-based risk-stratification. Our results illustrate the importance of considering genotyping error as a source of PGS error especially for cohorts with varying genotyping technologies and/or low-coverage sequencing.

Impact of cross-ancestry genetic architecture on GWASs in admixed populations.

Genome-wide association studies (GWASs) have identified thousands of variants for disease risk. These studies have predominantly been conducted in individuals of European ancestries, which raises questions about their transferability to individuals of other ancestries. Of particular interest are admixed populations, usually defined as populations with recent ancestry from two or more continental sources. Admixed genomes contain segments of distinct ancestries that vary in composition across individuals in the population, allowing for the same allele to induce risk for disease on different ancestral backgrounds. This mosaicism raises unique challenges for GWASs in admixed populations, such as the need to correctly adjust for population stratification. In this work we quantify the impact of differences in estimated allelic effect sizes for risk variants between ancestry backgrounds on association statistics. Specifically, while the possibility of estimated allelic effect-size heterogeneity by ancestry (HetLanc) can be modeled when performing a GWAS in admixed populations, the extent of HetLanc needed to overcome the penalty from an additional degree of freedom in the association statistic has not been thoroughly quantified. Using extensive simulations of admixed genotypes and phenotypes, we find that controlling for and conditioning effect sizes on local ancestry can reduce statistical power by up to 72%. This finding is especially pronounced in the presence of allele frequency differentiation. We replicate simulation results using 4,327 African-European admixed genomes from the UK Biobank for 12 traits to find that for most significant SNPs, HetLanc is not large enough for GWASs to benefit from modeling heterogeneity in this way.

A DNA methylation haplotype block landscape in human tissues and preimplantation embryos reveals regulatory elements defined by comethylation patterns.

DNA methylation and associated regulatory elements play a crucial role in gene expression regulation. Previous studies have focused primarily on the distribution of mean methylation levels. Advances in whole-genome bisulfite sequencing (WGBS) have enabled the characterization of DNA methylation haplotypes (MHAPs), representing CpG sites from the same read fragment on a single chromosome, and the subsequent identification of methylation haplotype blocks (MHBs), in which adjacent CpGs on the same fragment are comethylated. Using our expert-curated WGBS data sets, we report comprehensive landscapes of MHBs in 17 representative normal somatic human tissues and during early human embryonic development. Integrative analysis reveals MHBs as a distinctive type of regulatory element characterized by comethylation patterns rather than mean methylation levels. We show the enrichment of MHBs in open chromatin regions, tissue-specific histone marks, and enhancers, including super-enhancers. Moreover, we find that MHBs tend to localize near tissue-specific genes and show an association with differential gene expression that is independent of mean methylation. Similar findings are observed in the context of human embryonic development, highlighting the dynamic nature of MHBs during early development. Collectively, our comprehensive MHB landscapes provide valuable insights into the tissue specificity and developmental dynamics of DNA methylation.

Feeding induces cholesterol biosynthesis via the mTORC1-USP20-HMGCR axis.

Cholesterol is an essential lipid and its synthesis is nutritionally and energetically costly1,2. In mammals, cholesterol biosynthesis increases after feeding and is inhibited under fasting conditions3. However, the regulatory mechanisms of cholesterol biosynthesis at the fasting-feeding transition remain poorly understood. Here we show that the deubiquitylase ubiquitin-specific peptidase 20 (USP20) stabilizes HMG-CoA reductase (HMGCR), the rate-limiting enzyme in the cholesterol biosynthetic pathway, in the feeding state. The post-prandial increase in insulin and glucose concentration stimulates mTORC1 to phosphorylate USP20 at S132 and S134; USP20 is recruited to the HMGCR complex and antagonizes its degradation. The feeding-induced stabilization of HMGCR is abolished in mice with liver-specific Usp20 deletion and in USP20(S132A/S134A) knock-in mice. Genetic deletion or pharmacological inhibition of USP20 markedly decreases diet-induced body weight gain, reduces lipid levels in the serum and liver, improves insulin sensitivity and increases energy expenditure. These metabolic changes are reversed by expression of the constitutively stable HMGCR(K248R). This study reveals an unexpected regulatory axis from mTORC1 to HMGCR via USP20 phosphorylation and suggests that inhibitors of USP20 could be used to lower cholesterol levels to treat metabolic diseases including hyperlipidaemia, liver steatosis, obesity and diabetes.

Partitioning gene-level contributions to complex-trait heritability by allele frequency identifies disease-relevant genes.

Recent works have shown that SNP heritability-which is dominated by low-effect common variants-may not be the most relevant quantity for localizing high-effect/critical disease genes. Here, we introduce methods to estimate the proportion of phenotypic variance explained by a given assignment of SNPs to a single gene ("gene-level heritability"). We partition gene-level heritability by minor allele frequency (MAF) to find genes whose gene-level heritability is explained exclusively by "low-frequency/rare" variants (0.5% ≤ MAF < 1%). Applying our method to ∼16K protein-coding genes and 25 quantitative traits in the UK Biobank (N = 290K "White British"), we find that, on average across traits, ∼2.5% of nonzero-heritability genes have a rare-variant component and only ∼0.8% (327 gene-trait pairs) have heritability exclusively from rare variants. Of these 327 gene-trait pairs, 114 (35%) were not detected by existing gene-level association testing methods. The additional genes we identify are significantly enriched for known disease genes, and we find several examples of genes that have been previously implicated in phenotypically related Mendelian disorders. Notably, the rare-variant component of gene-level heritability exhibits trends different from those of common-variant gene-level heritability. For example, while total gene-level heritability increases with gene length, the rare-variant component is significantly larger among shorter genes; the cumulative distributions of gene-level heritability also vary across traits and reveal differences in the relative contributions of rare/common variants to overall gene-level polygenicity. While nonzero gene-level heritability does not imply causality, if interpreted in the correct context, gene-level heritability can reveal useful insights into complex-trait genetic architecture.

Classical swine fever virus non-structural protein 4A recruits dihydroorotate dehydrogenase to facilitate viral replication.

Mitochondria are energy producers in cells, which can affect viral replication by regulating the host innate immune signaling pathways, and the changes in their biological functions are inextricably linked the viral life cycle. In this study, we screened a library of 382 mitochondria-targeted compounds and identified the antiviral inhibitors of dihydroorotate dehydrogenase (DHODH), the rate-limiting enzyme in the de novo synthesis pathway of pyrimidine ribonucleotides, against classical swine fever virus (CSFV). Our data showed that the inhibitors interfered with viral RNA synthesis in a dose-dependent manner, with half-maximal effective concentrations (EC50) ranging from 0.975 to 26.635 nM. Remarkably, DHODH inhibitors obstructed CSFV replication by enhancing the innate immune response including the TBK1-IRF3-STAT1 and NF-κB signaling pathways. Furthermore, the data from a series of compound addition and supplementation trials indicated that DHODH inhibitors also inhibited CSFV replication by blocking the de novo pyrimidine synthesis. Remarkably, DHODH knockdown demonstrated that it was essential for CSFV replication. Mechanistically, confocal microscopy and immunoprecipitation assays showed that the non-structural protein 4A (NS4A) recruited and interacted with DHODH in the perinuclear. Notably, NS4A enhanced the DHODH activity and promoted the generation of UMP for efficient viral replication. Structurally, the amino acids 65-229 of DHODH and the amino acids 25-40 of NS4A were pivotal for this interaction. Taken together, our findings highlight the critical role of DHODH in the CSFV life cycle and offer a potential antiviral target for the development of novel therapeutics against CSF. IMPORTANCE: Classical swine fever remains one of the most economically important viral diseases of domestic pigs and wild boar worldwide. dihydroorotate dehydrogenase (DHODH) inhibitors have been shown to suppress the replication of several viruses in vitro and in vivo, but the effects on Pestivirus remain unknown. In this study, three specific DHODH inhibitors, including DHODH-IN-16, BAY-2402234, and Brequinar were found to strongly suppress classical swine fever virus (CSFV) replication. These inhibitors target the host DHODH, depleting the pyrimidine nucleotide pool to exert their antiviral effects. Intriguingly, we observed that the non-structural protein 4A of CSFV induced DHODH to accumulate around the nucleus in conjunction with mitochondria. Moreover, NS4A exhibited a strong interaction with DHODH, enhancing its activity to promote efficient CSFV replication. In conclusion, our findings enhance the understanding of the pyrimidine synthesis in CSFV infection and expand the novel functions of CSFV NS4A in viral replication, providing a reference for further exploration of antiviral targets against CSFV.

TRAmHap: accurate prediction of transcriptional activity from DNA methylation haplotypes in bisulfite-sequencing data.

Deoxyribonucleic acid (DNA) methylation (DNAm) is an important epigenetic mechanism that plays a role in chromatin structure and transcriptional regulation. Elucidating the relationship between DNAm and gene expression is of great importance for understanding its role in transcriptional regulation. The conventional approach is to construct machine-learning-based methods to predict gene expression based on mean methylation signals in promoter regions. However, this type of strategy only explains about 25% of gene expression variation, and hence is inadequate in elucidating the relationship between DNAm and transcriptional activity. In addition, using mean methylation as input features neglects the heterogeneity of cell populations that can be reflected by DNAm haplotypes. We here developed TRAmaHap, a novel deep-learning framework that predicts gene expression by utilizing the characteristics of DNAm haplotypes in proximal promoters and distal enhancers. Using benchmark data of human and mouse normal tissues, TRAmHap shows much higher accuracy than existing machine-learning based methods, by explaining 60~80% of gene expression variation across tissue types and disease conditions. Our model demonstrated that gene expression can be accurately predicted by DNAm patterns in promoters and long-range enhancers as far as 25 kb away from transcription start site, especially in the presence of intra-gene chromatin interactions.

Comprehensive pan-cancer analysis of the C2ORF40 expression: Infiltration associations and prognostic implications.

In recent years, C2ORF40 has been identified as a tumor suppressor gene with multiple functions, including roles in cell proliferation, migration, and senescence. To explore the role of the C2ORF40 gene in different tumors, we used multiple databases for analysis. Compared to adjacent normal tissues, C2ORF40 is downregulated in a variety of malignant tumors, including tumors such as breast cancer, colorectal cancer, bladder cancer, hepatocellular carcinoma and prostate cancer. Notably, low expression of the gene is significantly associated with poor overall survival and relapse-free survival rates. In specific cancers including colon cancer and prostate cancer, the expression of C2ORF40 is correlated with the infiltration of CAFs. C2ORF40 is also involved in biological processes such as cell apoptosis and regulation of protein stability. In conclusion, C2ORF40 can hold promise as a prognostic marker for pan-cancer analysis.

Author Correction: c-MAF-dependent regulatory T cells mediate immunological tolerance to a gut pathobiont.

In this Letter, the 'Competing interests' statement should have stated: 'D.R.L. consults for and has equity in Vedanta Biosciences.' The original Letter has not been corrected.