A single-cell atlas of chromatin accessibility in the human genome.

Current catalogs of regulatory sequences in the human genome are still incomplete and lack cell type resolution. To profile the activity of gene regulatory elements in diverse cell types and tissues in the human body, we applied single-cell chromatin accessibility assays to 30 adult human tissue types from multiple donors. We integrated these datasets with previous single-cell chromatin accessibility data from 15 fetal tissue types to reveal the status of open chromatin for ∼1.2 million candidate cis-regulatory elements (cCREs) in 222 distinct cell types comprised of >1.3 million nuclei. We used these chromatin accessibility maps to delineate cell-type-specificity of fetal and adult human cCREs and to systematically interpret the noncoding variants associated with complex human traits and diseases. This rich resource provides a foundation for the analysis of gene regulatory programs in human cell types across tissues, life stages, and organ systems.

Integration of multi-omics data and deep phenotyping enables prediction of cytokine responses.

The immune response to pathogens varies substantially among people. Whereas both genetic and nongenetic factors contribute to interperson variation, their relative contributions and potential predictive power have remained largely unknown. By systematically correlating host factors in 534 healthy volunteers, including baseline immunological parameters and molecular profiles (genome, metabolome and gut microbiome), with cytokine production after stimulation with 20 pathogens, we identified distinct patterns of co-regulation. Among the 91 different cytokine-stimulus pairs, 11 categories of host factors together explained up to 67% of interindividual variation in cytokine production induced by stimulation. A computational model based on genetic data predicted the genetic component of stimulus-induced cytokine production (correlation 0.28-0.89), and nongenetic factors influenced cytokine production as well.

DNA methylation atlas of the mouse brain at single-cell resolution.

Mammalian brain cells show remarkable diversity in gene expression, anatomy and function, yet the regulatory DNA landscape underlying this extensive heterogeneity is poorly understood. Here we carry out a comprehensive assessment of the epigenomes of mouse brain cell types by applying single-nucleus DNA methylation sequencing1,2 to profile 103,982 nuclei (including 95,815 neurons and 8,167 non-neuronal cells) from 45 regions of the mouse cortex, hippocampus, striatum, pallidum and olfactory areas. We identified 161 cell clusters with distinct spatial locations and projection targets. We constructed taxonomies of these epigenetic types, annotated with signature genes, regulatory elements and transcription factors. These features indicate the potential regulatory landscape supporting the assignment of putative cell types and reveal repetitive usage of regulators in excitatory and inhibitory cells for determining subtypes. The DNA methylation landscape of excitatory neurons in the cortex and hippocampus varied continuously along spatial gradients. Using this deep dataset, we constructed an artificial neural network model that precisely predicts single neuron cell-type identity and brain area spatial location. Integration of high-resolution DNA methylomes with single-nucleus chromatin accessibility data3 enabled prediction of high-confidence enhancer-gene interactions for all identified cell types, which were subsequently validated by cell-type-specific chromatin conformation capture experiments4. By combining multi-omic datasets (DNA methylation, chromatin contacts, and open chromatin) from single nuclei and annotating the regulatory genome of hundreds of cell types in the mouse brain, our DNA methylation atlas establishes the epigenetic basis for neuronal diversity and spatial organization throughout the mouse cerebrum.

An atlas of gene regulatory elements in adult mouse cerebrum.

The mammalian cerebrum performs high-level sensory perception, motor control and cognitive functions through highly specialized cortical and subcortical structures1. Recent surveys of mouse and human brains with single-cell transcriptomics2-6 and high-throughput imaging technologies7,8 have uncovered hundreds of neural cell types distributed in different brain regions, but the transcriptional regulatory programs that are responsible for the unique identity and function of each cell type remain unknown. Here we probe the accessible chromatin in more than 800,000 individual nuclei from 45 regions that span the adult mouse isocortex, olfactory bulb, hippocampus and cerebral nuclei, and use the resulting data to map the state of 491,818 candidate cis-regulatory DNA elements in 160 distinct cell types. We find high specificity of spatial distribution for not only excitatory neurons, but also most classes of inhibitory neurons and a subset of glial cell types. We characterize the gene regulatory sequences associated with the regional specificity within these cell types. We further link a considerable fraction of the cis-regulatory elements to putative target genes expressed in diverse cerebral cell types and predict transcriptional regulators that are involved in a broad spectrum of molecular and cellular pathways in different neuronal and glial cell populations. Our results provide a foundation for comprehensive analysis of gene regulatory programs of the mammalian brain and assist in the interpretation of noncoding risk variants associated with various neurological diseases and traits in humans.

Genetic insights into biological mechanisms governing human ovarian ageing.

Reproductive longevity is essential for fertility and influences healthy ageing in women1,2, but insights into its underlying biological mechanisms and treatments to preserve it are limited. Here we identify 290 genetic determinants of ovarian ageing, assessed using normal variation in age at natural menopause (ANM) in about 200,000 women of European ancestry. These common alleles were associated with clinical extremes of ANM; women in the top 1% of genetic susceptibility have an equivalent risk of premature ovarian insufficiency to those carrying monogenic FMR1 premutations3. The identified loci implicate a broad range of DNA damage response (DDR) processes and include loss-of-function variants in key DDR-associated genes. Integration with experimental models demonstrates that these DDR processes act across the life-course to shape the ovarian reserve and its rate of depletion. Furthermore, we demonstrate that experimental manipulation of DDR pathways highlighted by human genetics increases fertility and extends reproductive life in mice. Causal inference analyses using the identified genetic variants indicate that extending reproductive life in women improves bone health and reduces risk of type 2 diabetes, but increases the risk of hormone-sensitive cancers. These findings provide insight into the mechanisms that govern ovarian ageing, when they act, and how they might be targeted by therapeutic approaches to extend fertility and prevent disease.

An integrative genomics approach identifies KDM4 as a modulator of trained immunity.

Innate immune cells are able to build memory characteristics via a process termed "trained immunity." Host factors that influence the magnitude of the individual trained immunity response remain largely unknown. Using an integrative genomics approach, our study aimed to prioritize and understand the role of specific genes in trained immunity responses. In vitro-induced trained immunity responses were assessed in two independent population-based cohorts of healthy individuals, the 300 Bacillus Calmette-Guérin (300BCG; n = 267) and 200 Functional Genomics (200FG; n = 110) cohorts from the Human Functional Genomics Project. Genetic loci that influence cytokine responses upon trained immunity were identified by conducting a meta-analysis of QTLs identified in the 300BCG and 200FG cohorts. From the identified QTL loci, we functionally validated the role of PI3K-Akt signaling pathway and two genes that belong to the family of Siglec receptors (Siglec-5 and Siglec-14). Furthermore, we identified the H3K9 histone demethylases of the KDM4 family as major regulators of trained immunity responses. These data pinpoint an important role of metabolic and epigenetic processes in the regulation of trained immunity responses, and these findings may open new avenues for vaccine design and therapeutic interventions.

Profiling Parkinson's disease cognitive phenotypes via resting-state magnetoencephalography.

Aberrant brain oscillations are a hallmark of Parkinson's disease (PD) pathophysiology and may be related to both motor and nonmotor symptoms. Mild cognitive impairment (MCI) affects many people with PD even at the time of diagnosis and conversion risks to PD dementia (PDD) are very high. Unfortunately, pharmacotherapies are not addressing cognitive symptoms in PD. Profiling PD cognitive phenotypes (e.g., MCI, PDD, etc.) may therefore help inform future treatments. Neurophysiological methods, such as magnetoencephalography (MEG), offer the advantage of observing oscillatory patterns, whose regional and temporal profiles may elucidate how cognitive changes relate to neural mechanisms. We conducted a resting-state MEG cross-sectional study of 89 persons with PD stratified into three phenotypic groups: normal cognition, MCI, and PDD, to identify brain regions and frequencies most associated with each cognitive profile. In addition, a neuropsychological battery was administered to assess each domain of cognition. Our data showed higher power in lower frequency bands (delta and theta) observed along with more severe cognitive impairment and associated with memory, language, attention, and global cognition. Of the total 119 brain parcels assessed during source analysis, widespread group differences were found in the beta band, with significant changes mostly occurring between the normal cognition and MCI groups. Moreover, bilateral frontal and left-hemispheric regions were particularly affected in the other frequencies as cognitive decline becomes more pronounced. Our results suggest that MCI and PDD may be qualitatively distinct cognitive phenotypes, and most dramatic changes seem to have happened when the PD brain shows mild cognitive decline.NEW & NOTEWORTHY Can we better stage cognitive decline in patients with Parkinson's disease (PD)? Here, we provide evidence that mild cognitive impairment, rather than being simply a milder form of dementia, may be a qualitatively distinct phase in its development. We suggest that the most dramatic neurophysiological changes may occur during the time the PD brain transitions from normal cognition to MCI, then compensatory changes further occur as the brain "switches" to a dementia state.

Integrating GWAS with bulk and single-cell RNA-sequencing reveals a role for LY86 in the anti-Candida host response.

Candida bloodstream infection, i.e. candidemia, is the most frequently encountered life-threatening fungal infection worldwide, with mortality rates up to almost 50%. In the majority of candidemia cases, Candida albicans is responsible. Worryingly, a global increase in the number of patients who are susceptible to infection (e.g. immunocompromised patients), has led to a rise in the incidence of candidemia in the last few decades. Therefore, a better understanding of the anti-Candida host response is essential to overcome this poor prognosis and to lower disease incidence. Here, we integrated genome-wide association studies with bulk and single-cell transcriptomic analyses of immune cells stimulated with Candida albicans to further our understanding of the anti-Candida host response. We show that differential expression analysis upon Candida stimulation in single-cell expression data can reveal the important cell types involved in the host response against Candida. This confirmed the known major role of monocytes, but more interestingly, also uncovered an important role for NK cells. Moreover, combining the power of bulk RNA-seq with the high resolution of single-cell RNA-seq data led to the identification of 27 Candida-response QTLs and revealed the cell types potentially involved herein. Integration of these response QTLs with a GWAS on candidemia susceptibility uncovered a potential new role for LY86 in candidemia susceptibility. Finally, experimental follow-up confirmed that LY86 knockdown results in reduced monocyte migration towards the chemokine MCP-1, thereby implying that this reduced migration may underlie the increased susceptibility to candidemia. Altogether, our integrative systems genetics approach identifies previously unknown mechanisms underlying the immune response to Candida infection.

Deconvolution of bulk blood eQTL effects into immune cell subpopulations.

BACKGROUND: Expression quantitative trait loci (eQTL) studies are used to interpret the function of disease-associated genetic risk factors. To date, most eQTL analyses have been conducted in bulk tissues, such as whole blood and tissue biopsies, which are likely to mask the cell type-context of the eQTL regulatory effects. Although this context can be investigated by generating transcriptional profiles from purified cell subpopulations, current methods to do this are labor-intensive and expensive. We introduce a new method, Decon2, as a framework for estimating cell proportions using expression profiles from bulk blood samples (Decon-cell) followed by deconvolution of cell type eQTLs (Decon-eQTL). RESULTS: The estimated cell proportions from Decon-cell agree with experimental measurements across cohorts (R ≥ 0.77). Using Decon-cell, we could predict the proportions of 34 circulating cell types for 3194 samples from a population-based cohort. Next, we identified 16,362 whole-blood eQTLs and deconvoluted cell type interaction (CTi) eQTLs using the predicted cell proportions from Decon-cell. CTi eQTLs show excellent allelic directional concordance with eQTL (≥ 96-100%) and chromatin mark QTL (≥87-92%) studies that used either purified cell subpopulations or single-cell RNA-seq, outperforming the conventional interaction effect. CONCLUSIONS: Decon2 provides a method to detect cell type interaction effects from bulk blood eQTLs that is useful for pinpointing the most relevant cell type for a given complex disease. Decon2 is available as an R package and Java application (https://github.com/molgenis/systemsgenetics/tree/master/Decon2) and as a web tool (www.molgenis.org/deconvolution).

Author Correction: In vitro virucidal activity of Echinaforce®, an Echinacea purpurea preparation, against coronaviruses, including common cold coronavirus 229E and SARS-CoV-2.

The original version of the acknowledgement unfortunately contained a mistake.

In vitro virucidal activity of Echinaforce®, an Echinacea purpurea preparation, against coronaviruses, including common cold coronavirus 229E and SARS-CoV-2.

BACKGROUND: Coronaviruses (CoVs) were long thought to only cause mild respiratory and gastrointestinal symptoms in humans but outbreaks of Middle East Respiratory Syndrome (MERS)-CoV, Severe Acute Respiratory Syndrome (SARS)-CoV-1, and the recently identified SARS-CoV-2 have cemented their zoonotic potential and their capacity to cause serious morbidity and mortality, with case fatality rates ranging from 4 to 35%. Currently, no specific prophylaxis or treatment is available for CoV infections. Therefore we investigated the virucidal and antiviral potential of Echinacea purpurea (Echinaforce®) against human coronavirus (HCoV) 229E, highly pathogenic MERS- and SARS-CoVs, as well as the newly identified SARS-CoV-2, in vitro. METHODS: To evaluate the antiviral potential of the extract, we pre-treated virus particles and cells and evaluated remaining infectivity by limited dilution. Furthermore, we exposed cells to the extract after infection to further evaluate its potential as a prophylaxis and treatment against coronaviruses. We also determined the protective effect of Echinaforce® in re-constituted nasal epithelium. RESULTS: In the current study, we found that HCoV-229E was irreversibly inactivated when exposed to Echinaforce® at 3.2 µg/ml IC50. Pre-treatment of cell lines, however, did not inhibit infection with HCoV-229E and post-infection treatment had only a marginal effect on virus propagation at 50 µg/ml. However, we did observe a protective effect in an organotypic respiratory cell culture system by exposing pre-treated respiratory epithelium to droplets of HCoV-229E, imitating a natural infection. The observed virucidal activity of Echinaforce® was not restricted to common cold coronaviruses, as both SARS-CoV-1 and MERS-CoVs were inactivated at comparable concentrations. Finally, the causative agent of COVID-19, SARS-CoV-2 was also inactivated upon treatment with 50µg/ml Echinaforce®. CONCLUSIONS: These results show that Echinaforce® is virucidal against HCoV-229E, upon direct contact and in an organotypic cell culture model. Furthermore, MERS-CoV and both SARS-CoV-1 and SARS-CoV-2 were inactivated at similar concentrations of the extract. Therefore we hypothesize that Echinacea purpurea preparations, such as Echinaforce®, could be effective as prophylactic treatment for all CoVs due to their structural similarities.

Reduced nondominant lumbar multifidi cross-sectional area is a precursor of low back injury in cricket fast bowlers.

Asymmetry in the lumbar multifidi muscle (LM) cross-sectional area (CSA) is associated with low back injury. The aim of this prospective cohort study was to investigate the symmetry of the CSA of LM at L3, L4, and L5, in the context of simultaneous injury monitoring. Injury free, male, right-handed cricket fast bowlers playing at a nonprofessional level participated in this study. LM CSA at L3, L4, and L5 vertebral levels was measured through the use of ultrasound imaging in prone. The primary outcome measure of the study was the incidence of an injury during a cricket season of eight-month duration. Twenty-six fast bowlers (aged 21.8 ± 1.8 years) participated. No difference was found between the nondominant and the dominant LM CSA among injury free bowlers (P>.05). However, in bowlers who sustained a lower back injury during the cricket season, the nondominant CSA at L3 (nondominant median 5.80 cm2 , range 3.69 cm2 ; dominant median 7.38 cm2 , range 2.61 cm2 ; P=.04) and L5 (nondominant median 6.94 cm2 , range 2.10 cm2 ; dominant median 7.38 cm2 , range 3.54 cm2 ; P=.04) is smaller compared to the dominant side. These findings may indicate that a side-to-side difference in LM CSA may be a precursor of injury.

Third-generation smallpox vaccines induce low-level cross-protecting neutralizing antibodies against Monkeypox virus in laboratory workers.

Due to the discontinuation of routine smallpox vaccination after its eradication in 1980, a large part of the human population remains naïve against smallpox and other members of the orthopoxvirus genus. As a part of biosafety personnel protection programs, laboratory workers receive prophylactic vaccinations against diverse infectious agents, including smallpox. Here, we studied the levels of cross-protecting neutralizing antibodies as well as total IgG induced by either first- or third-generation smallpox vaccines against Monkeypox virus, using a clinical isolate from the 2022 outbreak. Serum neutralization tests indicated better overall neutralization capacity after vaccination with first-generation smallpox vaccines, compared to an attenuated third-generation vaccine. Results obtained from total IgG ELISA, however, did not show higher induction of orthopoxvirus-specific IgGs in first-generation vaccine recipients. Taken together, our results indicate a lower level of cross-protecting neutralizing antibodies against Monkeypox virus in recipients of third-generation smallpox vaccine compared to first-generation vaccine recipients, although total IgG levels were comparable.

Co-expression in tissue-specific gene networks links genes in cancer-susceptibility loci to known somatic driver genes.

BACKGROUND: The genetic background of cancer remains complex and challenging to integrate. Many somatic mutations within genes are known to cause and drive cancer, while genome-wide association studies (GWAS) of cancer have revealed many germline risk factors associated with cancer. However, the overlap between known somatic driver genes and positional candidate genes from GWAS loci is surprisingly small. We hypothesised that genes from multiple independent cancer GWAS loci should show tissue-specific co-regulation patterns that converge on cancer-specific driver genes. RESULTS: We studied recent well-powered GWAS of breast, prostate, colorectal and skin cancer by estimating co-expression between genes and subsequently prioritising genes that show significant co-expression with genes mapping within susceptibility loci from cancer GWAS. We observed that the prioritised genes were strongly enriched for cancer drivers defined by COSMIC, IntOGen and Dietlein et al. The enrichment of known cancer driver genes was most significant when using co-expression networks derived from non-cancer samples of the relevant tissue of origin. CONCLUSION: We show how genes within risk loci identified by cancer GWAS can be linked to known cancer driver genes through tissue-specific co-expression networks. This provides an important explanation for why seemingly unrelated sets of genes that harbour either germline risk factors or somatic mutations can eventually cause the same type of disease.

Enhlink infers distal and context-specific enhancer-promoter linkages.

Enhlink is a computational tool for scATAC-seq data analysis, facilitating precise interrogation of enhancer function at the single-cell level. It employs an ensemble approach incorporating technical and biological covariates to infer condition-specific regulatory DNA linkages. Enhlink can integrate multi-omic data for enhanced specificity, when available. Evaluation with simulated and real data, including multi-omic datasets from the mouse striatum and novel promoter capture Hi-C data, demonstrate that Enhlink outperfoms alternative methods. Coupled with eQTL analysis, it identified a putative super-enhancer in striatal neurons. Overall, Enhlink offers accuracy, power, and potential for revealing novel biological insights in gene regulation.

Kinematic differences between left- and right-handed cricket fast bowlers during the bowling action.

Background: Despite differences between left- and right-handed athletes in other sports, minimal evidence exists regarding biomechanical similarities and differences between left- and right-handed cricket fast bowlers performing an equivalent task. Objectives: This study aimed to compare the kinematics between left and right-handed fast bowlers performing an equivalent task (i.e. bowling 'over the wicket' to a batter of the same handedness as the bowler). Methods: Full body, three-dimensional kinematic data for six left-handed and 20 right-handed adolescent, male, fast bowlers were collected using the Xsens inertial measurement system. Time-normalised joint and segment angle time histories from back foot contact to follow-through ground contacts were compared between groups via statistical parametric mapping. Whole movement and subphase durations were also compared. Results: Left-handed players displayed significantly more trunk flexion from 49%-56% of the total movement (ball release occurred at 54%; p = 0.037) and had shorter back foot contact durations on average (0.153 vs 0.177 s; p = 0.036) compared to right-handed players. Conclusion: Left- and right-handed bowlers displayed similar sagittal plane kinematics but appeared to use non-sagittal plane movements differently around the time of ball release. The kinematic differences identified in this study can inform future research investigating the effect of hand dominance on bowling performance and injury risk.

Enhlink infers distal and context-specific enhancer-promoter linkages.

Enhancers play a crucial role in regulating gene expression and their functional status can be queried with cell type precision using using single-cell (sc)ATAC-seq. To facilitate analysis of such data, we developed Enhlink, a novel computational approach that leverages single-cell signals to infer linkages between regulatory DNA sequences, such as enhancers and promoters. Enhlink uses an ensemble strategy that integrates cell-level technical covariates to control for batch effects and biological covariates to infer robust condition-specific links and their associated p-values. It can integrate simultaneous gene expression and chromatin accessibility measurements of individual cells profiled by multi-omic experiments for increased specificity. We evaluated Enhlink using simulated and real scATAC-seq data, including those paired with physical enhancer-promoter links enumerated by promoter capture Hi-C and with multi-omic scATAC-/RNA-seq data we generated from the mouse striatum. These examples demonstrated that our method outperforms popular alternative strategies. In conjunction with eQTL analysis, Enhlink revealed a putative super-enhancer regulating key cell type-specific markers of striatal neurons. Taken together, our analyses demonstrate that Enhlink is accurate, powerful, and provides features that can lead to novel biological insights.

Virucidal activity of three standard chemical disinfectants against Ebola virus suspended in tripartite soil and whole blood.

Proper disinfection and inactivation of highly pathogenic viruses is an essential component of public health and prevention. Depending on environment, surfaces, and type of contaminant, various methods of disinfection must be both efficient and available. To test both established and novel chemical disinfectants against risk group 4 viruses in our maximum containment facility, we developed a standardized protocol and assessed the chemical inactivation of the two Ebola virus variants Mayinga and Makona suspended in two different biological soil loads. Standard chemical disinfectants ethanol and sodium hypochlorite completely inactivate both Ebola variants after 30 s in suspension at 70% and 0.5% v/v, respectively, concentrations recommended for disinfection by the World Health Organization. Additionally, peracetic acid is also inactivating at 0.2% v/v under the same conditions. Continued vigilance and optimization of current disinfection protocols is extremely important due to the continuous presence of Ebola virus on the African continent and increased zoonotic spillover of novel viral pathogens. Furthermore, to facilitate general pandemic preparedness, the establishment and sharing of standardized protocols is very important as it allows for rapid testing and evaluation of novel pathogens and chemical disinfectants.

Robust enhancer-gene regulation identified by single-cell transcriptomes and epigenomes.

Single-cell sequencing could help to solve the fundamental challenge of linking millions of cell-type-specific enhancers with their target genes. However, this task is confounded by patterns of gene co-expression in much the same way that genetic correlation due to linkage disequilibrium confounds fine-mapping in genome-wide association studies (GWAS). We developed a non-parametric permutation-based procedure to establish stringent statistical criteria to control the risk of false-positive associations in enhancer-gene association studies (EGAS). We applied our procedure to large-scale transcriptome and epigenome data from multiple tissues and species, including the mouse and human brain, to predict enhancer-gene associations genome wide. We tested the functional validity of our predictions by comparing them with chromatin conformation data and causal enhancer perturbation experiments. Our study shows how controlling for gene co-expression enables robust enhancer-gene linkage using single-cell sequencing data.

Brain expression quantitative trait locus and network analyses reveal downstream effects and putative drivers for brain-related diseases.

Identification of therapeutic targets from genome-wide association studies (GWAS) requires insights into downstream functional consequences. We harmonized 8,613 RNA-sequencing samples from 14 brain datasets to create the MetaBrain resource and performed cis- and trans-expression quantitative trait locus (eQTL) meta-analyses in multiple brain region- and ancestry-specific datasets (n ≤ 2,759). Many of the 16,169 cortex cis-eQTLs were tissue-dependent when compared with blood cis-eQTLs. We inferred brain cell types for 3,549 cis-eQTLs by interaction analysis. We prioritized 186 cis-eQTLs for 31 brain-related traits using Mendelian randomization and co-localization including 40 cis-eQTLs with an inferred cell type, such as a neuron-specific cis-eQTL (CYP24A1) for multiple sclerosis. We further describe 737 trans-eQTLs for 526 unique variants and 108 unique genes. We used brain-specific gene-co-regulation networks to link GWAS loci and prioritize additional genes for five central nervous system diseases. This study represents a valuable resource for post-GWAS research on central nervous system diseases.