Computationally guided AAV engineering for enhanced gene delivery.

Gene delivery vehicles based on adeno-associated viruses (AAVs) are enabling increasing success in human clinical trials, and they offer the promise of treating a broad spectrum of both genetic and non-genetic disorders. However, delivery efficiency and targeting must be improved to enable safe and effective therapies. In recent years, considerable effort has been invested in creating AAV variants with improved delivery, and computational approaches have been increasingly harnessed for AAV engineering. In this review, we discuss how computationally designed AAV libraries are enabling directed evolution. Specifically, we highlight approaches that harness sequences outputted by next-generation sequencing (NGS) coupled with machine learning (ML) to generate new functional AAV capsids and related regulatory elements, pushing the frontier of what vector engineering and gene therapy may achieve.

A high-resolution enhancer atlas of the developing telencephalon.

The mammalian telencephalon plays critical roles in cognition, motor function, and emotion. Though many of the genes required for its development have been identified, the distant-acting regulatory sequences orchestrating their in vivo expression are mostly unknown. Here, we describe a digital atlas of in vivo enhancers active in subregions of the developing telencephalon. We identified more than 4,600 candidate embryonic forebrain enhancers and studied the in vivo activity of 329 of these sequences in transgenic mouse embryos. We generated serial sets of histological brain sections for 145 reproducible forebrain enhancers, resulting in a publicly accessible web-based data collection comprising more than 32,000 sections. We also used epigenomic analysis of human and mouse cortex tissue to directly compare the genome-wide enhancer architecture in these species. These data provide a primary resource for investigating gene regulatory mechanisms of telencephalon development and enable studies of the role of distant-acting enhancers in neurodevelopmental disorders.

Origin of life-forming volatile elements in the inner Solar System.

Volatile elements such as hydrogen, carbon, nitrogen and oxygen are essential ingredients to build habitable worlds like Earth, but their origin and evolution on terrestrial planets remain highly debated. Here we discuss the processes that distributed these elements throughout the early Solar System and how they then became incorporated into planetary building blocks. Volatiles on Earth and the other terrestrial planets appear to have been heterogeneously sourced from different Solar System reservoirs. The sources of planetary volatiles and the timing at which they were accreted to growing planets probably play a crucial role in controlling planet habitability.

Estimating heritability explained by local ancestry and evaluating stratification bias in admixture mapping from summary statistics.

The heritability explained by local ancestry markers in an admixed population (hγ2) provides crucial insight into the genetic architecture of a complex disease or trait. Estimation of hγ2 can be susceptible to biases due to population structure in ancestral populations. Here, we present heritability estimation from admixture mapping summary statistics (HAMSTA), an approach that uses summary statistics from admixture mapping to infer heritability explained by local ancestry while adjusting for biases due to ancestral stratification. Through extensive simulations, we demonstrate that HAMSTA hγ2 estimates are approximately unbiased and are robust to ancestral stratification compared to existing approaches. In the presence of ancestral stratification, we show a HAMSTA-derived sampling scheme provides a calibrated family-wise error rate (FWER) of ∼5% for admixture mapping, unlike existing FWER estimation approaches. We apply HAMSTA to 20 quantitative phenotypes of up to 15,988 self-reported African American individuals in the Population Architecture using Genomics and Epidemiology (PAGE) study. We observe hˆγ2 in the 20 phenotypes range from 0.0025 to 0.033 (mean hˆγ2 = 0.012 ± 9.2 × 10-4), which translates to hˆ2 ranging from 0.062 to 0.85 (mean hˆ2 = 0.30 ± 0.023). Across these phenotypes we find little evidence of inflation due to ancestral population stratification in current admixture mapping studies (mean inflation factor of 0.99 ± 0.001). Overall, HAMSTA provides a fast and powerful approach to estimate genome-wide heritability and evaluate biases in test statistics of admixture mapping studies.

Optogenetic control of Wnt signaling models cell-intrinsic embryogenic patterning using 2D human pluripotent stem cell culture.

In embryonic stem cell (ESC) models for early development, spatially and temporally varying patterns of signaling and cell types emerge spontaneously. However, mechanistic insight into this dynamic self-organization is limited by a lack of methods for spatiotemporal control of signaling, and the relevance of signal dynamics and cell-to-cell variability to pattern emergence remains unknown. Here, we combine optogenetic stimulation, imaging and transcriptomic approaches to study self-organization of human ESCs (hESC) in two-dimensional (2D) culture. Morphogen dynamics were controlled via optogenetic activation of canonical Wnt/ß-catenin signaling (optoWnt), which drove broad transcriptional changes and mesendoderm differentiation at high efficiency (>99% cells). When activated within cell subpopulations, optoWnt induced cell self-organization into distinct epithelial and mesenchymal domains, mediated by changes in cell migration, an epithelial to mesenchymal-like transition and TGFß signaling. Furthermore, we demonstrate that such optogenetic control of cell subpopulations can be used to uncover signaling feedback mechanisms between neighboring cell types. These findings reveal that cell-to-cell variability in Wnt signaling is sufficient to generate tissue-scale patterning and establish a hESC model system for investigating feedback mechanisms relevant to early human embryogenesis.

Murine MHC-Deficient Nonobese Diabetic Mice Carrying Human HLA-DQ8 Develop Severe Myocarditis and Myositis in Response to Anti-PD-1 Immune Checkpoint Inhibitor Cancer Therapy.

Myocarditis has emerged as an immune-related adverse event of immune checkpoint inhibitor (ICI) cancer therapy associated with significant mortality. To ensure patients continue to safely benefit from life-saving cancer therapy, an understanding of fundamental immunological phenomena underlying ICI myocarditis is essential. We recently developed the NOD-cMHCI/II-/-.DQ8 mouse model that spontaneously develops myocarditis with lower mortality than observed in previous HLA-DQ8 NOD mouse strains. Our strain was rendered murine MHC class I and II deficient using CRISPR/Cas9 technology, making it a genetically clean platform for dissecting CD4+ T cell-mediated myocarditis in the absence of classically selected CD8+ T cells. These mice are highly susceptible to myocarditis and acute heart failure following anti-PD-1 ICI-induced treatment. Additionally, anti-PD-1 administration accelerates skeletal muscle myositis. Using histology, flow cytometry, adoptive transfers, and RNA sequencing analyses, we performed a thorough characterization of cardiac and skeletal muscle T cells, identifying shared and unique characteristics of both populations. Taken together, this report details a mouse model with features of a rare, but highly lethal clinical presentation of overlapping myocarditis and myositis following ICI therapy. This study sheds light on underlying immunological mechanisms in ICI myocarditis and provides the basis for further detailed analyses of diagnostic and therapeutic strategies.

Network news: innovations in 21st century systems biology.

A decade ago, seminal perspectives and papers set a strong vision for the field of systems biology, and a number of these themes have flourished. Here, we describe key technologies and insights that have elucidated the evolution, architecture, and function of cellular networks, ultimately leading to the first predictive genome-scale regulatory and metabolic models of organisms. Can systems approaches bridge the gap between correlative analysis and mechanistic insights?

Development and evolution of the human neocortex.

The size and surface area of the mammalian brain are thought to be critical determinants of intellectual ability. Recent studies show that development of the gyrated human neocortex involves a lineage of neural stem and transit-amplifying cells that forms the outer subventricular zone (OSVZ), a proliferative region outside the ventricular epithelium. We discuss how proliferation of cells within the OSVZ expands the neocortex by increasing neuron number and modifying the trajectory of migrating neurons. Relating these features to other mammalian species and known molecular regulators of the mouse neocortex suggests how this developmental process could have emerged in evolution.

Phosphorylation of the nuclear poly(A) binding protein (PABPN1) during mitosis protects mRNA from hyperadenylation and maintains transcriptome dynamics.

Polyadenylation controls mRNA biogenesis, nucleo-cytoplasmic export, translation and decay. These processes are interdependent and coordinately regulated by poly(A)-binding proteins (PABPs), yet how PABPs are themselves regulated is not fully understood. Here, we report the discovery that human nuclear PABPN1 is phosphorylated by mitotic kinases at four specific sites during mitosis, a time when nucleoplasm and cytoplasm mix. To understand the functional consequences of phosphorylation, we generated a panel of stable cell lines inducibly over-expressing PABPN1 with point mutations at these sites. Phospho-inhibitory mutations decreased cell proliferation, highlighting the importance of PABPN1 phosphorylation in cycling cells. Dynamic regulation of poly(A) tail length and RNA stability have emerged as important modes of gene regulation. We therefore employed long-read sequencing to determine how PABPN1 phospho-site mutants affected poly(A) tails lengths and TimeLapse-seq to monitor mRNA synthesis and decay. Widespread poly(A) tail lengthening was observed for phospho-inhibitory PABPN1 mutants. In contrast, expression of phospho-mimetic PABPN1 resulted in shorter poly(A) tails with increased non-A nucleotides, in addition to increased transcription and reduced stability of a distinct cohort of mRNAs. Taken together, PABPN1 phosphorylation remodels poly(A) tails and increases mRNA turnover, supporting the model that enhanced transcriptome dynamics reset gene expression programs across the cell cycle.

Mechanosensitive stem cell fate choice is instructed by dynamic fluctuations in activation of Rho GTPases.

During the intricate process by which cells give rise to tissues, embryonic and adult stem cells are exposed to diverse mechanical signals from the extracellular matrix (ECM) that influence their fate. Cells can sense these cues in part through dynamic generation of protrusions, modulated and controlled by cyclic activation of Rho GTPases. However, it remains unclear how extracellular mechanical signals regulate Rho GTPase activation dynamics and how such rapid, transient activation dynamics are integrated to yield long-term, irreversible cell fate decisions. Here, we report that ECM stiffness cues alter not only the magnitude but also the temporal frequency of RhoA and Cdc42 activation in adult neural stem cells (NSCs). Using optogenetics to control the frequency of RhoA and Cdc42 activation, we further demonstrate that these dynamics are functionally significant, where high- vs. low-frequency activation of RhoA and Cdc42 drives astrocytic vs. neuronal differentiation, respectively. In addition, high-frequency Rho GTPase activation induces sustained phosphorylation of the TGFß pathway effector SMAD1, which in turn drives the astrocytic differentiation. By contrast, under low-frequency Rho GTPase stimulation, cells fail to accumulate SMAD1 phosphorylation and instead undergo neurogenesis. Our findings reveal the temporal patterning of Rho GTPase signaling and the resulting accumulation of an SMAD1 signal as a critical mechanism through which ECM stiffness cues regulate NSC fate.

Deletion of Vß3+CD4+ T cells by endogenous mouse mammary tumor virus 3 prevents type 1 diabetes induction by autoreactive CD8+ T cells.

In both humans and NOD mice, type 1 diabetes (T1D) develops from the autoimmune destruction of pancreatic beta cells by T cells. Interactions between both helper CD4+ and cytotoxic CD8+ T cells are essential for T1D development in NOD mice. Previous work has indicated that pathogenic T cells arise from deleterious interactions between relatively common genes which regulate aspects of T cell activation/effector function (Ctla4, Tnfrsf9, Il2/Il21), peptide presentation (H2-A g7, B2m), and T cell receptor (TCR) signaling (Ptpn22). Here, we used a combination of subcongenic mapping and a CRISPR/Cas9 screen to identify the NOD-encoded mammary tumor virus (Mtv)3 provirus as a genetic element affecting CD4+/CD8+ T cell interactions through an additional mechanism, altering the TCR repertoire. Mtv3 encodes a superantigen (SAg) that deletes the majority of Vß3+ thymocytes in NOD mice. Ablating Mtv3 and restoring Vß3+ T cells has no effect on spontaneous T1D development in NOD mice. However, transferring Mtv3 to C57BL/6 (B6) mice congenic for the NOD H2 g7 MHC haplotype (B6.H2 g7) completely blocks their normal susceptibility to T1D mediated by transferred CD8+ T cells transgenically expressing AI4 or NY8.3 TCRs. The entire genetic effect is manifested by Vß3+CD4+ T cells, which unless deleted by Mtv3, accumulate in insulitic lesions triggering in B6 background mice the pathogenic activation of diabetogenic CD8+ T cells. Our findings provide evidence that endogenous Mtv SAgs can influence autoimmune responses. Furthermore, since most common mouse strains have gaps in their TCR Vß repertoire due to Mtvs, it raises questions about the role of Mtvs in other mouse models designed to reflect human immune disorders.

Neutral or detrimental effects of TREM2 agonist antibodies in preclinical models of Alzheimer's Disease and Multiple Sclerosis.

Human genetics and preclinical studies have identified key contributions of TREM2 to several neurodegenerative conditions, inspiring efforts to modulate TREM2 therapeutically. Here, we characterize the activities of three TREM2 agonist antibodies in multiple mixed-sex mouse models of Alzheimer's Disease (AD) pathology and remyelination. Receptor activation and downstream signaling are explored in vitro, and active dose ranges are determined in vivo based on pharmacodynamic responses from microglia. For mice bearing amyloid-ß (Aß) pathology (PS2APP) or combined Aß and tau pathology (TauPS2APP), chronic TREM2 agonist antibody treatment had limited impact on microglia engagement with pathology, overall pathology burden, or downstream neuronal damage. For mice with demyelinating injuries triggered acutely with lysolecithin, TREM2 agonist antibodies unexpectedly disrupted injury resolution. Likewise, TREM2 agonist antibodies limited myelin recovery for mice experiencing chronic demyelination from cuprizone. We highlight the contributions of dose timing and frequency across models. These results introduce important considerations for future TREM2-targeting approaches.Significance Statement Multiple TREM2 agonist antibodies are investigated in mouse models of Alzheimer's Disease and Multiple Sclerosis. Despite agonism in culture models and after acute dosing in mice, antibodies do not show benefit in overall AD pathology and worsen recovery after demyelination.

Hierarchical joint analysis of marginal summary statistics-Part II: High-dimensional instrumental analysis of omics data.

Instrumental variable (IV) analysis has been widely applied in epidemiology to infer causal relationships using observational data. Genetic variants can also be viewed as valid IVs in Mendelian randomization and transcriptome-wide association studies. However, most multivariate IV approaches cannot scale to high-throughput experimental data. Here, we leverage the flexibility of our previous work, a hierarchical model that jointly analyzes marginal summary statistics (hJAM), to a scalable framework (SHA-JAM) that can be applied to a large number of intermediates and a large number of correlated genetic variants-situations often encountered in modern experiments leveraging omic technologies. SHA-JAM aims to estimate the conditional effect for high-dimensional risk factors on an outcome by incorporating estimates from association analyses of single-nucleotide polymorphism (SNP)-intermediate or SNP-gene expression as prior information in a hierarchical model. Results from extensive simulation studies demonstrate that SHA-JAM yields a higher area under the receiver operating characteristics curve (AUC), a lower mean-squared error of the estimates, and a much faster computation speed, compared to an existing approach for similar analyses. In two applied examples for prostate cancer, we investigated metabolite and transcriptome associations, respectively, using summary statistics from a GWAS for prostate cancer with more than 140,000 men and high dimensional publicly available summary data for metabolites and transcriptomes.

Hierarchical joint analysis of marginal summary statistics-Part I: Multipopulation fine mapping and credible set construction.

Recent advancement in genome-wide association studies (GWAS) comes from not only increasingly larger sample sizes but also the shift in focus towards underrepresented populations. Multipopulation GWAS increase power to detect novel risk variants and improve fine-mapping resolution by leveraging evidence and differences in linkage disequilibrium (LD) from diverse populations. Here, we expand upon our previous approach for single-population fine-mapping through Joint Analysis of Marginal SNP Effects (JAM) to a multipopulation analysis (mJAM). Under the assumption that true causal variants are common across studies, we implement a hierarchical model framework that conditions on multiple SNPs while explicitly incorporating the different LD structures across populations. The mJAM framework can be used to first select index variants using the mJAM likelihood with different feature selection approaches. In addition, we present a novel approach leveraging the ideas of mediation to construct credible sets for these index variants. Construction of such credible sets can be performed given any existing index variants. We illustrate the implementation of the mJAM likelihood through two implementations: mJAM-SuSiE (a Bayesian approach) and mJAM-Forward selection. Through simulation studies based on realistic effect sizes and levels of LD, we demonstrated that mJAM performs well for constructing concise credible sets that include the underlying causal variants. In real data examples taken from the most recent multipopulation prostate cancer GWAS, we showed several practical advantages of mJAM over other existing multipopulation methods.

Clonal hematopoiesis and risk of prostate cancer in large samples of European ancestry men.

Little is known regarding the potential relationship between clonal hematopoiesis (CH) of indeterminate potential (CHIP), which is the expansion of hematopoietic stem cells with somatic mutations, and risk of prostate cancer, the fifth leading cause of cancer death of men worldwide. We evaluated the association of age-related CHIP with overall and aggressive prostate cancer risk in two large whole-exome sequencing studies of 75 047 European ancestry men, including 7663 prostate cancer cases, 2770 of which had aggressive disease, and 3266 men carrying CHIP variants. We found that CHIP, defined by over 50 CHIP genes individually and in aggregate, was not significantly associated with overall (aggregate HR = 0.93, 95% CI = 0.76-1.13, P = 0.46) or aggressive (aggregate OR = 1.14, 95% CI = 0.92-1.41, P = 0.22) prostate cancer risk. CHIP was weakly associated with genetic risk of overall prostate cancer, measured using a polygenic risk score (OR = 1.05 per unit increase, 95% CI = 1.01-1.10, P = 0.01). CHIP was not significantly associated with carrying pathogenic/likely pathogenic/deleterious variants in DNA repair genes, which have previously been found to be associated with aggressive prostate cancer. While findings from this study suggest that CHIP is likely not a risk factor for prostate cancer, it will be important to investigate other types of CH in association with prostate cancer risk.

Multi-ancestry fine-mapping improves precision to identify causal genes in transcriptome-wide association studies.

Transcriptome-wide association studies (TWASs) are a powerful approach to identify genes whose expression is associated with complex disease risk. However, non-causal genes can exhibit association signals due to confounding by linkage disequilibrium (LD) patterns and eQTL pleiotropy at genomic risk regions, which necessitates fine-mapping of TWAS signals. Here, we present MA-FOCUS, a multi-ancestry framework for the improved identification of genes underlying traits of interest. We demonstrate that by leveraging differences in ancestry-specific patterns of LD and eQTL signals, MA-FOCUS consistently outperforms single-ancestry fine-mapping approaches with equivalent total sample sizes across multiple metrics. We perform TWASs for 15 blood traits using genome-wide summary statistics (average nEA = 511 k, nAA = 13 k) and lymphoblastoid cell line eQTL data from cohorts of primarily European and African continental ancestries. We recapitulate evidence demonstrating shared genetic architectures for eQTL and blood traits between the two ancestry groups and observe that gene-level effects correlate 20% more strongly across ancestries than SNP-level effects. Lastly, we perform fine-mapping using MA-FOCUS and find evidence that genes at TWAS risk regions are more likely to be shared across ancestries than they are to be ancestry specific. Using multiple lines of evidence to validate our findings, we find that gene sets produced by MA-FOCUS are more enriched in hematopoietic categories than alternative approaches (p = 2.36 × 10-15). Our work demonstrates that including and appropriately accounting for genetic diversity can drive more profound insights into the genetic architecture of complex traits.

Biphasic Npas4 expression promotes inhibitory plasticity and suppression of fear memory consolidation in mice.

Long-term memories are believed to be encoded by unique transcriptional signatures in the brain. The expression of immediate early genes (IEG) promotes structural and molecular changes required for memory consolidation. Recent evidence has shown that the brain is equipped with mechanisms that not only promote, but actively constrict memory formation. However, it remains unknown whether IEG expression may play a role in memory suppression. Here we uncovered a novel function of the IEG neuronal PAS domain protein 4 (Npas4), as an inducible memory suppressor gene of highly salient aversive experiences. Using a contextual fear conditioning paradigm, we found that low stimulus salience leads to monophasic Npas4 expression, while highly salient learning induces a biphasic expression of Npas4 in the hippocampus. The later phase requires N-methyl-D-aspartate (NMDA) receptor activity and is independent of dopaminergic neurotransmission. Our in vivo pharmacological and genetic manipulation experiments suggested that the later phase of Npas4 expression restricts the consolidation of a fear memory and promote behavioral flexibility, by facilitating fear extinction and the contextual specificity of fear responses. Moreover, immunofluorescence and electrophysiological analysis revealed a concomitant increase in synaptic input from cholecystokinin (CCK)-expressing interneurons. Our results demonstrate how salient experiences evoke unique temporal patterns of IEG expression that fine-tune memory consolidation. Moreover, our study provides evidence for inducible gene expression associated with memory suppression as a possible mechanism to balance the consolidation of highly salient memories, and thereby to evade the formation of maladaptive behavior.

Heterogeneity of Islet-Infiltrating IL-21+ CD4 T Cells in a Mouse Model of Type 1 Diabetes.

IL-21 is essential for type 1 diabetes (T1D) development in the NOD mouse model. IL-21-expressing CD4 T cells are present in pancreatic islets where they contribute to T1D progression. However, little is known about their phenotype and differentiation states. To fill this gap, we generated, to our knowledge, a novel IL-21 reporter NOD strain to further characterize IL-21+ CD4 T cells in T1D. IL-21+ CD4 T cells accumulate in pancreatic islets and recognize ß cell Ags. Single-cell RNA sequencing revealed that CD4 T effector cells in islets actively express IL-21 and they are highly diabetogenic despite expressing multiple inhibitory molecules, including PD-1 and LAG3. Islet IL-21+ CD4 T cells segregate into four phenotypically and transcriptionally distinct differentiation states, that is, less differentiated early effectors, T follicular helper (Tfh)-like cells, and two Th1 subsets. Trajectory analysis predicts that early effectors differentiate into both Tfh-like and terminal Th1 cells. We further demonstrated that intrinsic IL-27 signaling controls the differentiation of islet IL-21+ CD4 T cells, contributing to their helper function. Collectively, our study reveals the heterogeneity of islet-infiltrating IL-21+ CD4 T cells and indicates that both Tfh-like and Th1 subsets produce IL-21 throughout their differentiation process, highlighting the important sources of IL-21 in T1D pathogenesis.

HLA-DQ8 Supports Development of Insulitis Mediated by Insulin-Reactive Human TCR-Transgenic T Cells in Nonobese Diabetic Mice.

In an effort to improve HLA-"humanized" mouse models for type 1 diabetes (T1D) therapy development, we previously generated directly in the NOD strain CRISPR/Cas9-mediated deletions of various combinations of murine MHC genes. These new models improved upon previously available platforms by retaining ß2-microglobulin functionality in FcRn and nonclassical MHC class I formation. As proof of concept, we generated H2-Db/H2-Kd double knockout NOD mice expressing human HLA-A*0201 or HLA-B*3906 class I variants that both supported autoreactive diabetogenic CD8+ T cell responses. In this follow-up work, we now describe the creation of 10 new NOD-based mouse models expressing various combinations of HLA genes with and without chimeric transgenic human TCRs reactive to proinsulin/insulin. The new TCR-transgenic models develop differing levels of insulitis mediated by HLA-DQ8-restricted insulin-reactive T cells. Additionally, these transgenic T cells can transfer insulitis to newly developed NSG mice lacking classical murine MHC molecules, but expressing HLA-DQ8. These new models can be used to test potential therapeutics for a possible capacity to reduce islet infiltration or change the phenotype of T cells expressing type 1 diabetes patient-derived ß cell autoantigen-specific TCRs.

Geochemical evidence for high volatile fluxes from the mantle at the end of the Archaean.

The exchange of volatile species-water, carbon dioxide, nitrogen and halogens-between the mantle and the surface of the Earth has been a key driver of environmental changes throughout Earth's history. Degassing of the mantle requires partial melting and is therefore linked to mantle convection, whose regime and vigour in the Earth's distant past remain poorly constrained1,2. Here we present direct geochemical constraints on the flux of volatiles from the mantle. Atmospheric xenon has a monoisotopic excess of 129Xe, produced by the decay of extinct 129I. This excess was mainly acquired during Earth's formation and early evolution3, but mantle degassing has also contributed 129Xe to the atmosphere through geological time. Atmospheric xenon trapped in samples from the Archaean eon shows a slight depletion of 129Xe relative to the modern composition4,5, which tends to disappear in more recent samples5,6. To reconcile this deficit in the Archaean atmosphere by mantle degassing would require the degassing rate of Earth at the end of the Archaean to be at least one order of magnitude higher than today. We demonstrate that such an intense activity could not have occurred within a plate tectonics regime. The most likely scenario is a relatively short (about 300 million years) burst of mantle activity at the end of the Archaean (around 2.5 billion years ago). This lends credence to models advocating a magmatic origin for drastic environmental changes during the Neoarchaean era, such as the Great Oxidation Event.