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The Peranakan Chinese are culturally unique descendants of immigrants from China who settled in the Malay Archipelago ∼300–500 years ago. Today, among large communities in Southeast Asia, the Peranakans have preserved Chinese traditions with strong influence from the local indigenous Malays. Yet, whether or to what extent genetic admixture co-occurred with the cultural mixture has been a topic of ongoing debate. We performed whole-genome sequencing (WGS) on 177 Singapore (SG) Peranakans and analyzed the data jointly with WGS data of Asian and European populations. We estimated that Peranakan Chinese inherited ∼5.62% (95% confidence interval [CI]: 4.76–6.49%) Malay ancestry, much higher than that in SG Chinese (1.08%, 0.65–1.51%), southern Chinese (0.86%, 0.50–1.23%), and northern Chinese (0.25%, 0.18–0.32%). A sex-biased admixture history, in which the Malay ancestry was contributed primarily by females, was supported by X chromosomal variants, and mitochondrial (MT) and Y haplogroups. Finally, we identified an ancient admixture event shared by Peranakan Chinese and SG Chinese ∼1,612 (95% CI: 1,345–1,923) years ago, coinciding with the settlement history of Han Chinese in southern China, apart from the recent admixture event with Malays unique to Peranakan Chinese ∼190 (159–213) years ago. These findings greatly advance our understanding of the dispersal history of Chinese and their interaction with indigenous populations in Southeast Asia.

In flowering plants, the tapetum cells in anthers undergo programmed cell death (PCD) at the late meiotic stage, providing nutrients for further development of microspores, including the formation of the pollen wall. However, the molecular basis of tapetum PCD remains elusive. Here we report a tapetum PCD-related mutant in rice (Oryza sativa), earlier degraded tapetum 1 (edt1), that shows complete pollen abortion associated with earlier-than-programmed tapetum cell death. EDT1 encodes a subunit of ATP-citrate lyase (ACL), and is specifically expressed in the tapetum of anthers. EDT1 localized in both the nucleus and the cytoplasm as observed in rice protoplast transient assays. We demonstrated that the A and B subunits of ACL interacted with each other and might function as a heteromultimer in the cytoplasm. EDT1 catalyzes the critical steps in cytosolic acetyl-CoA synthesis. Our data indicated a decrease in ATP level, energy charge, and fatty acid content in mutant edt1 anthers. In addition, the genes encoding secretory proteases or lipid transporters, and the transcription factors known to regulate PCD, were downregulated. Our results demonstrate that the timing of tapetum PCD must be tightly regulated for successful pollen development, and that EDT1 is involved in the tapetum PCD process. This study furthers our understanding of the molecular basis of pollen fertility and fecundity in rice and may also be relevant to other flowering plants.

Anther dehiscence, one of the essential steps in pollination and double fertilization, is regulated by a complex signaling pathway encompassing hormones and environmental factors. However, key components underlying the signaling pathway that regulate anther dehiscence remain largely elusive. Here, we isolated a rice mutant anther dehiscence defected 1 (Osadd1) that exhibited defects in anther dehiscence and glume open. Map-based cloning revealed that OsADD1 encoded a GARP (Golden2, ARR-B and Psr1) transcription factor. Sequence analysis showed that a single base deletion in Osadd1 mutant resulted in pre-termination of the GARP domain. OsADD1 was constitutively expressed in various tissues, with more abundance in the panicles. The major genes associated with anther dehiscence were affected in the Osadd1 mutant, and the expression level of the cellulose synthase-like D sub-family 4 (OsCSLD4) was significantly decreased. We demonstrate that OsADD1 regulated the expression of OsCSLD4 by binding to its promoter, and affects rice anther dehiscence.

Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P-8), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution.A trans-ancestry meta-analysis of GWAS of glycemic traits in up to 281,416 individuals identifies 99 novel loci, of which one quarter was found due to the multi-ancestry approach, which also improves fine-mapping of credible variant sets.

Background Mounting evidence suggests that circulating microRNAs (miRNAs) are critical indicators of cardiovascular disease. However, prospective studies linking circulating miRNAs to incident acute coronary syndrome (ACS) are limited, and the underlying effect of associated miRNA on incident ACS remains unknown. Methods and Results Based on a 2‐stage prospective nested case–control design within the Dongfeng‐Tongji cohort, we profiled plasma miRNAs from 23 pairs of incident ACS cases and controls by microarray and validated the candidate miRNAs in 572 incident ACS case–control pairs using quantitative real‐time polymerase chain reaction. We observed that plasma miR‐4286 was associated with higher risk of ACS (adjusted odds ratio according to an interquartile range increase, 1.26 [95% CI, 1.07–1.48]). Further association analysis revealed that triglyceride was positively associated with plasma miR‐4286, and an interquartile range increase in triglyceride was associated with an 11.04% (95% CI, 3.77%–18.83%) increase in plasma miR‐4286. In addition, the Mendelian randomization analysis suggested a potential causal effect of triglyceride on plasma miR‐4286 ( β coefficients: 0.27 [95% CI, 0.01–0.53] and 0.27 [95% CI, 0.07–0.47] separately by inverse variance‐weighted and Mendelian randomization‐pleiotropy residual sum and outlier tests). Moreover, the causal mediation analysis indicated that plasma miR‐4286 explained 5.5% (95% CI, 0.7%–17.0%) of the association of triglyceride with incident ACS. Conclusions Higher level of plasma miR‐4286 was associated with an increased risk of ACS. The upregulated miR‐4286 in plasma can be attributed to higher triglyceride level and may mediate the effect of triglyceride on incident ACS.

Chromosomes are segmented into domains and compartments; yet, how these structures are spatially related in 3D is unclear. Here, by directly integrating Hi-C capture experiments and 3D modeling, we use X-inactivation as a model to examine the time evolution of 3D chromosome architecture during substantial changes in gene expression. First, we show that gene expression A/B compartments are consistent with phase separation in 3D space. Second, we show that residuals of smaller scale structures persist through transitions, despite further large-scale reorganization into the final inactive configuration, comprising two “megadomains”. Interestingly, these previously hidden residual structures were not detectable in 2D Hi-C maps or principal component analyses. Third, time-dependent reaction-diffusion simulations reveal how Xist RNA particles diffuse across the 3D X-superstructure as it reorganizes. Our 4DHiC pipeline helps satisfy the growing demand for methodologies that produce 3D chromosome reconstructions directly from 2D datasets, which are consistent with the empirical data.

Knowledge is limited about the patterns of viral persistence and host response in patients with COVID-19. This large study from Wuhan, China, reports longitudinal data on viral positivity as well the patterns of antibody and inflammatory response during the course of COVID-19. These data would be valuable for developing effective preventive and treatment strategies against COVID-19., Background: The understanding of viral positivity and seroconversion during the course of coronavirus disease 2019 (COVID-19) is limited. Objective: To describe patterns of viral polymerase chain reaction (PCR) positivity and evaluate their correlations with seroconversion and disease severity. Design: Retrospective cohort study. Setting: 3 designated specialty care centers for COVID-19 in Wuhan, China. Participants: 3192 adult patients with COVID-19. Measurements: Demographic, clinical, and laboratory data. Results: Among 12 780 reverse transcriptase PCR tests for severe acute respiratory syndrome coronavirus 2 that were done, 24.0% had positive results. In 2142 patients with laboratory-confirmed COVID-19, the viral positivity rate peaked within the first 3 days. The median duration of viral positivity was 24.0 days (95% CI, 18.9 to 29.1 days) in critically ill patients and 18.0 days (CI, 16.8 to 19.1 days) in noncritically ill patients. Being critically ill was an independent risk factor for longer viral positivity (hazard ratio, 0.700 [CI, 0.595 to 0.824]; P < 0.001). In patients with laboratory-confirmed COVID-19, the IgM-positive rate was 19.3% in the first week, peaked in the fifth week (81.5%), and then decreased steadily to around 55% within 9 to 10 weeks. The IgG-positive rate was 44.6% in the first week, reached 93.3% in the fourth week, and then remained high. Similar antibody responses were seen in clinically diagnosed cases. Serum inflammatory markers remained higher in critically ill patients. Among noncritically ill patients, a higher proportion of those with persistent viral positivity had low IgM titers (

BackgroundAlthough the association between mouth ulcers and psychiatric traits has been reported by observational studies, their causal relationship remains unclear. Mendelian randomization (MR), powered by large-scale genome-wide association studies (GWAS), provides an opportunity to clarify the causality between mouth ulcers and psychiatric traits.MethodsWe collected summary statistics of mouth ulcers (sample size n = 461,106) and 10 psychiatric traits from the largest publicly available GWAS on Europeans, including anxiety disorder (n = 83,566), attention deficit/hyperactivity disorder (n = 53,293), autism spectrum disorder (n = 46,350), bipolar disorder (n = 51,710), insomnia (n = 1,331,010), major depressive disorder (n = 480,359), mood instability (n = 363,705), neuroticism (n = 168,105), schizophrenia (n = 105,318), and subjective wellbeing (n = 388,538). We applied three two-sample bi-directional MR analysis methods, namely the Inverse Variance Weighted (IVW) method, the MR pleiotropy residual sum and outlier (MR-PRESSO) method, and the weighted median method, to assess the causal relationship between each psychiatric trait and mouth ulcers.ResultsWe found significant effects of autism spectrum disorder, insomnia, major depressive disorder, and subjective wellbeing on mouth ulcers, with the corresponding odds ratio (OR) from the IVW method being 1.160 [95% confidence interval (CI): 1.066–1.261, P = 5.39 × 10–4], 1.092 (1.062–1.122, P = 3.37 × 10–10), 1.234 (1.134–1.342, P = 1.03 × 10–6), and 0.703 (0.571–0.865, P = 8.97 × 10–4), respectively. We also observed suggestive evidence for mood instability to cause mouth ulcers [IVW, OR = 1.662 (1.059–2.609), P = 0.027]. These results were robust to weak instrument bias and heterogeneity. We found no evidence on causal effects between other psychiatric traits and mouth ulcers, in either direction.ConclusionOur findings suggest a protective effect of subjective wellbeing and risk effects of autism spectrum disorder, insomnia, major depressive disorder, and mood instability on mouth ulcers. These results clarify the causal relationship between psychiatric traits and the development of mouth ulcers.

Glycaemic traits are used to diagnose and monitor type 2 diabetes, and cardiometabolic health. To date, most genetic studies of glycaemic traits have focused on individuals of European ancestry. Here, we aggregated genome-wide association studies in up to 281,416 individuals without diabetes (30% non-European ancestry) with fasting glucose, 2h-glucose post-challenge, glycated haemoglobin, and fasting insulin data. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P-8), 80% with no significant evidence of between-ancestry heterogeneity. Analyses restricted to European ancestry individuals with equivalent sample size would have led to 24 fewer new loci. Compared to single-ancestry, equivalent sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase understanding of diabetes pathophysiology by use of trans-ancestry studies for improved power and resolution.

Context Glycated hemoglobin A1c (HbA1c) level is used to screen and diagnose diabetes. Genetic determinants of HbA1c can vary across populations and many of the genetic variants influencing HbA1c level were specific to populations. Objective To discover genetic variants associated with HbA1c level in nondiabetic Malay individuals. Design and Participants We conducted a genome-wide association study (GWAS) analysis for HbA1c using 2 Malay studies, the Singapore Malay Eye Study (SiMES, N = 1721 on GWAS array) and the Living Biobank study (N = 983 on GWAS array and whole-exome sequenced). We built a Malay-specific reference panel to impute ethnic-specific variants and validate the associations with HbA1c at ethnic-specific variants. Results Meta-analysis of the 1000 Genomes imputed array data identified 4 loci at genome-wide significance (P Conclusion We identified a deletion at SLC4A1 associated with HbA1c in Malay. The nonglycemic lowering of HbA1c at rs769664228 might cause individuals carrying this variant to be underdiagnosed for diabetes or prediabetes when HbA1c is used as the only diagnostic test for diabetes.

The tumour stroma regulates nearly all stages of carcinogenesis. Stromal heterogeneity in human triple-negative breast cancers (TNBCs) remains poorly understood, limiting the development of stromal-targeted therapies. Single cell RNA-sequencing of five TNBCs revealed two cancer-associated fibroblast (CAF) and two perivascular-like (PVL) subpopulations. CAFs clustered into two states, the first with features of myofibroblasts and the second characterised by high expression of growth factors and immunomodulatory molecules. PVL cells clustered into two states consistent with a differentiated and immature phenotype. We showed that these stromal states have distinct morphologies, spatial relationships and functional properties in regulating the extracellular matrix. Using cell-signalling predictions, we provide evidence that stromal-immune crosstalk acts via a diverse array of immunoregulatory molecules. Importantly, the investigation of gene signatures from inflammatory-CAFs and differentiated-PVL cells in independent TNBC patient cohorts revealed strong associations with cytotoxic T-cell dysfunction and exclusion, respectively. Such insights present promising candidates to further investigate for new therapeutic strategies in the treatment of TNBCs.

Vigorous non-pharmaceutical interventions have largely suppressed the COVID-19 outbreak in Wuhan, China. We developed a susceptible-exposed-infectious-recovered model to study the transmission dynamics and evaluate the impact of interventions using 32,583 laboratory-confirmed cases from December 8, 2019 till March 8, 2020, accounting for time-varying ascertainment rates, transmission rates, and population movements. The effective reproductive number R0 dropped from 3.89 (95% credible interval: 3.79-4.00) before intervention to 0.14 (0.11-0.28) after full-scale multi-8 pronged interventions. By projection, the interventions reduced the total infections in Wuhan by 96.5% till March 8. Furthermore, we estimated that 79% (lower bound: 60%) of the total infections were unascertained, potentially including asymptomatic and mild-symptomatic cases. The probability of resurgence was 0.22 and 0.10 based on models with 79% and 60% infections unascertained, respectively, assuming interventions were lifted after a 14-day period of no new ascertained infections. These results provide important implications for continuing surveillance and interventions to eventually contain the outbreak.

Background: To compare clinical features between moderate and severe cases with COVID-19, and screen factors associated with disease severity.Methods: Demographic and clinical data were compared between moderate and severe cases. Logistic regression was performed for prognostic factors.Results: 163 patients (median age 65.0 (56.8-71.0) years, 78 (47.9%) females) were enrolled, including 87 (53.4%) severe and 76 (46.6%) moderate cases. 79 (90.8%) severe and 59 (77.6%) moderate cases had comorbidities, with hypertension and diabetes commonly presented. The most common symptoms were fever. Severe cases had higher lactate dehydrogenase (LDH), inflammatory cytokines and lymphopenia, eosinopenia on admission, and lower eosinophil and higher neutrophil counts from admission to day 13 and 19. Multivariable regression showed that neutrophilia, eosinopenia, high LDH and D-dimer were associated with severe COVID-19. In receiver operating characteristic curve analysis, LDH, eosinophil and neutrophil + eosinophil + LDH + D-dimer combination, with area under curve of 0.86, 0.76 and 0.93, predicted severe illness with high sensitivity (82.8%, 83.3%, 88.0%) and specificity (68.4%, 84.2%, 81.3%).Conclusions: Eosinopenia, higher LDH and neutrophil + eosinophil + LDH + D-dimer combination on admission were powerful indicators of severe COVID-19. Dynamic changes of neutrophils and eosinophils may be used to evaluate disease progression.

ObjectiveHemoglobin A1c (HbA1c) accuracy is important for diabetes diagnosis and estimation of overall glycemia. The G6PD-Asahi variant which causes glucose-6-phosphate dehydrogenase (G6PD) deficiency has been shown to lower HbA1c independently of glycemia in African ancestry populations. As different G6PD variants occur in Asian ancestry, we sought to identify Asian-specific G6PD variants associated with HbA1c.Research design and methodsIn eight Asian population-based cohorts, we performed imputation on the X chromosome using the 1000 Genomes reference panel and tested for association with HbA1c (10 005 East Asians and 2051 South Asians). Results were meta-analyzed across studies. We compared the proportion of individuals classified as having diabetes/pre-diabetes by fasting glucose ≥100 mg/dL or HbA1c ≥5.7% units among carriers and non-carriers of HbA1c-associated variants.ResultsThe strongest association was a missense variant (G6PD-Canton, rs72554665, minor allele frequency=2.2%, effect in men=−0.76% unit, 95% CI −0.88 to −0.64, p=1.25×10−27, n=2844). Conditional analyses identified a secondary distinct signal, missense variant (G6PD-Kaiping, rs72554664, minor allele frequency=1.6%, effect in men=−1.12 % unit, 95% CI −1.32 to −0.92, p=3.12×10−15, pconditional_Canton=7.57×10−11). Adjusting for glucose did not attenuate their effects. The proportion of individuals with fasting glucose ≥100 mg/dL did not differ by carrier status of G6PD-Canton (p=0.21). Whereas the proportion of individuals with HbA1c ≥5.7% units was lower in carriers (5%) compared with non-carriers of G6PD-Canton (30%, p=0.03).ConclusionsWe identified two G6PD variants in East Asian men associated with non-glycemic lowering of HbA1c. Carriers of these variants are more likely to be underdiagnosed for diabetes or pre-diabetes than non-carriers if screened by HbA1c without confirmation by direct glucose measurements.

Liver, a heterogeneous tissue consisting of various cell types, is known to be relevant for blood lipid traits. By integrating summary statistics from genome-wide association studies (GWAS) of lipid traits and single-cell transcriptome data of the liver, we sought to identify specific cell types in the liver that were most relevant for blood lipid levels. We conducted differential expression analyses for 40 cell types from human and mouse livers in order to construct the cell-type specifically expressed gene sets, which we refer to as construction of the liver cell-type specifically expressed gene sets (CT-SEGS). Under the assumption that CT-SEGS represented specific functions of each cell type, we applied stratified linkage disequilibrium score regression to determine cell types that were most relevant for complex traits and diseases. We first confirmed the validity of this method (of delineating functionally relevant cell types) by identifying the immune cell types as relevant for autoimmune diseases. We further showed that lipid GWAS signals were enriched in the human and mouse periportal hepatocytes. Our results provide important information to facilitate future cellular studies of the metabolic mechanism affecting blood lipid levels.

BACKGROUNDWe described the epidemiological features of the coronavirus disease 2019 (Covid-19) outbreak, and evaluated the impact of non-pharmaceutical interventions on the epidemic in Wuhan, China.METHODSIndividual-level data on 25,961 laboratory-confirmed Covid-19 cases reported through February 18, 2020 were extracted from the municipal Notifiable Disease Report System. Based on key events and interventions, we divided the epidemic into four periods: before January 11, January 11-22, January 23 - February 1, and February 2-18. We compared epidemiological characteristics across periods and different demographic groups. We developed a susceptible-exposed-infectious-recovered model to study the epidemic and evaluate the impact of interventions.RESULTSThe median age of the cases was 57 years and 50.3% were women. The attack rate peaked in the third period and substantially declined afterwards across geographic regions, sex and age groups, except for children (age CONCLUSIONSConsiderable countermeasures have effectively controlled the Covid-19 outbreak in Wuhan. Special efforts are needed to protect vulnerable populations, including healthcare workers, elderly and children. Estimation of unascertained cases has important implications on continuing surveillance and interventions.

Summary Background Small airway dysfunction is a common but neglected respiratory abnormality. Little is known about its prevalence, risk factors, and prognostic factors in China or anywhere else in the world. We aimed to estimate the prevalence of small airway dysfunction using spirometry before and after bronchodilation, both overall and in specific population subgroups; assess its association with a range of lifestyle and environmental factors (particularly smoking); and estimate the burden of small airway dysfunction in China. Methods From June, 2012, to May, 2015, the nationally representative China Pulmonary Health study invited 57 779 adults to participate using a multistage stratified sampling method from ten provinces (or equivalent), and 50 479 patients with valid lung function testing results were included in the analysis. We diagnosed small airway dysfunction on the basis of at least two of the following three indicators of lung function being less than 65% of predicted: maximal mid-expiratory flow, forced expiratory flow (FEF) 50%, and FEF 75%. Small airway dysfunction was further categorised into pre-small airway dysfunction (defined as having normal FEV1 and FEV1/forced vital capacity [FVC] ratio before bronchodilator inhalation), and post-small airway dysfunction (defined as having normal FEV1 and FEV1/FVC ratio both before and after bronchodilator inhalation). Logistic regression yielded adjusted odds ratios (ORs) for small airway dysfunction associated with smoking and other lifestyle and environmental factors. We further estimated the total number of cases of small airway dysfunction in China by applying present study findings to national census data. Findings Overall the prevalence of small airway dysfunction was 43·5% (95% CI 40·7–46·3), pre-small airway dysfunction was 25·5% (23·6–27·5), and post-small airway dysfunction was 11·3% (10·3–12·5). After multifactor regression analysis, the risk of small airway dysfunction was significantly associated with age, gender, urbanisation, education level, cigarette smoking, passive smoking, biomass use, exposure to high particulate matter with a diameter less than 2·5 μm (PM2·5) concentrations, history of chronic cough during childhood, history of childhood pneumonia or bronchitis, parental history of respiratory diseases, and increase of body-mass index (BMI) by 5 kg/m2. The ORs for small airway dysfunction and pre-small airway dysfunction were similar, whereas larger effect sizes were generally seen for post-small airway dysfunction than for either small airway dysfunction or pre-small airway dysfunction. For post-small airway dysfunction, cigarette smoking, exposure to PM2·5, and increase of BMI by 5 kg/m2 were significantly associated with increased risk, among preventable risk factors. There was also a dose-response association between cigarette smoking and post-small airway dysfunction among men, but not among women. We estimate that, in 2015, 426 (95% CI 411–468) million adults had small airway dysfunction, 253 (238–278) million had pre-small airway dysfunction, and 111 (104–126) million had post-small airway dysfunction in China. Interpretation In China, spirometry-defined small airway dysfunction is highly prevalent, with cigarette smoking being a major modifiable risk factor, along with PM2·5 exposure and increase of BMI by 5 kg/m2. Our findings emphasise the urgent need to develop and implement effective primary and secondary prevention strategies to reduce the burden of this condition in the general population. Funding Ministry of Science and Technology of China; National Natural Science Foundation of China; National Health Commission of China.

Whole-exome sequencing (WES) has been widely used to study the role of protein-coding variants in genetic diseases. Non-coding regions, typically covered by sparse off-target data, are often discarded by conventional WES analyses. Here, we develop a genotype calling pipeline named WEScall to analyse both target and off-target data. We leverage linkage disequilibrium shared within study samples and from an external reference panel to improve genotyping accuracy. In an application to WES of 2527 Chinese and Malays, WEScall can reduce the genotype discordance rate from 0.26% (SE= 6.4 × 10−6) to 0.08% (SE = 3.6 × 10−6) across 1.1 million single nucleotide polymorphisms (SNPs) in the deeply sequenced target regions. Furthermore, we obtain genotypes at 0.70% (SE = 3.0 × 10−6) discordance rate across 5.2 million off-target SNPs, which had ~1.2× mean sequencing depth. Using this dataset, we perform genome-wide association studies of 10 metabolic traits. Despite of our small sample size, we identify 10 loci at genome-wide significance (P

Background: The association between mouth ulcers and psychiatric traits has been reported by observational studies. However, their causal relationship remains unclear. Methods: We collected summary statistics of mouth ulcers and ten psychiatric traits from the largest publicly available genome-wide association studies (GWAS) on Europeans, including anxiety disorder (sample size n=83,566), attention deficit/hyperactivity disorder (n=53,293), autism spectrum disorder (n=46,350), bipolar disorder (n=51,710), insomnia (n=1,331,010), major depressive disorder (n=480,359), mood instability (n=363,705), neuroticism (n=168,105), schizophrenia (n=105,318), and subjective well-being (n=388,538). For each psychiatric trait, we conducted two-sample bi-directional Mendelian randomization (MR) analyses to assess its causal relationship with mouth ulcers. Findings: We found strong evidence that autism spectrum disorder, insomnia, major depressive disorder, mood instability, and subjective well-being had causal effects on mouth ulcers, and the corresponding odds ratio (OR) (95% CI ) were 1.160 (95% CI : 1.066-1.261, P=5.39×10-4), 1.092 (1.062-1.122, P=3.37×10-10), 1.234 (1.134-1.342, P=1.03×10-6), 1.662 (1.059-2.609, P=0.027), and 0.703 (0.571-0.865, P=8.97×10-4), respectively. These results were robust to weak instrument bias and heterogeneity. We found no evidence on causal effects between other psychiatric traits and mouth ulcers, in either direction. Interpretation: Our findings suggest a protective effect of subjective well-being, and risk effects of autism spectrum disorder, insomnia, major depressive disorder, and mood instability on mouth ulcers. Our results clarify the causal relationship between psychiatric traits and the development of mouth ulcers. Funding Statement: This study was supported by the Natural Science Foundation of China (NSFC 81973148) and the Huazhong University of Science and Technology. Declaration of Interests: The authors declare no competing interests. Ethics Approval Statement: Because this study used published GWAS summary statistics available in the public domain, specific ethical review or consent from study participants was not sought.

Background: In December 2019, an ongoing outbreak of coronavirus disease 2019 (COVID-19) occurred in Wuhan, China While COVID-19 has become a global pandemic

Background: Early invasive ventilation can effectively improve oxygenation and delay the disease progression of critically ill patients with coronavirus disease

Although genome-wide association studies have greatly advanced our understanding of the contribution of common noncoding variants to leprosy susceptibility, protein-coding variants have not been systematically investigated. We carried out a three-stage genome-wide association study of protein-coding variants in Han Chinese, of whom were 7,048 leprosy patients and 14,398 were healthy control subjects. Seven coding variants of exome-wide significance were discovered, including two rare variants: rs145562243 in NCKIPSD ( P = 1.71 × 10 –9 , odds ratio [OR] = 4.35) and rs149308743 in CARD9 ( P = 2.09 × 10 –8 , OR = 4.75); three low-frequency variants: rs76418789 in IL23R ( P = 1.03 × 10 –10 , OR = 1.36), rs146466242 in FLG ( P = 3.39 × 10 –12 , OR = 1.45), and rs55882956 in TYK2 ( P = 1.04 × 10 –6 , OR = 1.30); and two common variants: rs780668 in SLC29A3 ( P = 2.17 × 10 –9 , OR = 1.14) and rs181206 in IL27 ( P = 1.08 × 10 –7 , OR = 0.83). Discovered protein-coding variants, particularly low-frequency and rare ones, showed involvement of skin barrier and endocytosis/phagocytosis/autophagy, in addition to known innate and adaptive immunity, in the pathogenesis of leprosy, highlighting the merits of protein-coding variant studies for complex diseases.

Summary Genome-wide association studies (GWAS) and next generation sequencing studies (NGSS) are often performed in family studies to improve power in identifying genetic variants that are associated with clinical phenotypes. Efficient analysis of genome-wide studies with familial data is challenging due to the difficulty in modeling shared but unmeasured genetic and/or environmental factors that cause dependencies among family members. Existing genetic association testing procedures for family studies largely rely on generalized estimating equations (GEE) or linear mixed-effects (LME) models. These procedures may fail to properly control for type I errors when the imposed model assumptions fail. In this article, we propose the Sequence Robust Association Test (SRAT), a fully rank-based, flexible approach that tests for association between a set of genetic variants and an outcome, while accounting for within-family correlation and adjusting for covariates. Comparing to existing methods, SRAT has the advantages of allowing for unknown correlation structures and weaker assumptions about the outcome distribution. We provide theoretical justifications for SRAT and show that SRAT includes the well-known Wilcoxon rank sum test as a special case. Extensive simulation studies suggest that SRAT provides better protection against type I error rate inflation, and could be much more powerful for settings with skewed outcome distribution than existing methods. For illustration, we also apply SRAT to the familial data from the Framingham Heart Study and Offspring Study to examine the association between an inflammatory marker and a few sets of genetic variants.

With advances in whole-genome sequencing (WGS) technology, more advanced statistical methods for testing genetic association with rare variants are being developed. Methods in which variants are grouped for analysis are also known as variant-set, gene-based, and aggregate unit tests. The burden test and sequence kernel association test (SKAT) are two widely used variant-set tests, which were originally developed for samples of unrelated individuals and later have been extended to family data with known pedigree structures. However, computationally efficient and powerful variant-set tests are needed to make analyses tractable in large-scale WGS studies with complex study samples. In this paper, we propose the variant-set mixed model association tests (SMMAT) for continuous and binary traits using the generalized linear mixed model framework. These tests can be applied to large-scale WGS studies involving samples with population structure and relatedness, such as in the National Heart, Lung, and Blood Institute's Trans-Omics for Precision Medicine (TOPMed) program. SMMATs share the same null model for different variant sets, and a virtue of this null model, which includes covariates only, is that it needs to be fit only once for all tests in each genome-wide analysis. Simulation studies show that all the proposed SMMATs correctly control type I error rates for both continuous and binary traits in the presence of population structure and relatedness. We also illustrate our tests in a real data example of analysis of plasma fibrinogen levels in the TOPMed program (n = 23,763), using the Analysis Commons, a cloud-based computing platform.

The chloroplast is an important organelle that performs photosynthesis as well as biosynthesis and storage of many metabolites. Aminoacyl-tRNA synthetases (aaRSs) are key enzymes in protein synthesis. However, the relationship between chloroplast development and aaRSs still remains unclear. In this study, we isolated a rice albino 1 (ra1) mutant through methane sulfonate (EMS) mutagenesis of rice japonica cultivar Ningjing 4 (Oryza sativa L.), which displayed albinic leaves in seedling stage due to abnormal chloroplast development. Compared with wild type (WT), ra1 showed significantly decreased levels of chlorophylls (Chl) and carotenoids (Car) in 2-week-old seedlings, which also showed obvious plastidic structural defects including abnormal thylakoid membrane structures and more osmiophilic particles. These defects caused albino phenotypes in seedlings. Map-based cloning revealed that RA1 gene encodes a glycyl-tRNA synthetase (GlyRS), which was confirmed by genetic complementation and knockout by Crispr/Cas9 technology. Sequence analysis showed that a single base mutation (T to A) occurred in the sixth exon of RA1 and resulted in a change from Isoleucine (Ile) to Lysine (Lys). Real-time PCR analyses showed that RA1 expression levels were constitutive in most tissues, but most abundant in the leaves and stems. By transient expression in Nicotiana benthamiana, we found that RA1 protein was localized in the chloroplast. Expression levels of chlorophyll biosynthesis and plastid development related genes were disordered in the ra1 mutant. RNA analysis revealed biogenesis of chloroplast rRNAs was abnormal in ra1. Meanwhile, western blotting showed that synthesis of proteins associated with plastid development was significantly repressed. These results suggest that RA1 is involved in early chloroplast development and establishment of the plastidic ribosome system in rice.

We propose a Corrected Goodness-of-Fit Index (CGFI) for model evaluation in Structural Equation Modeling (SEM). The CGFI is essentially a corrected index that takes into account model complexity and downward bias caused by small sample size. Using simulations based on pre-set SEM models, we compared the properties of CGFI, Goodness-of-Fit (GFI), and Adjusted Goodness-of-Fit Index (AGFI) under different settings of sample size, estimation method, magnitude of factor loadings, model complexity, and types and degrees of model misspecification. We find that the CGFI is more stable across different sample sizes and much more sensitive to detect model misspecification than the GFI and AGFI. We recommend a critical value of 0.90 for the proposed CGFI to evaluate the goodness of fit of SEM. Our proposed CGFI is easy to implement and can serve as a useful supplementary fit index to existing ones.

Publisher's version (útgefin grein)., Increased levels of the urinary albumin-to-creatinine ratio (UACR) are associated with higher risk of kidney disease progression and cardiovascular events, but underlying mechanisms are incompletely understood. Here, we conduct trans-ethnic (n = 564,257) and European-ancestry specific meta-analyses of genome-wide association studies of UACR, including ancestry- and diabetes-specific analyses, and identify 68 UACR-associated loci. Genetic correlation analyses and risk score associations in an independent electronic medical records database (n = 192,868) reveal connections with proteinuria, hyperlipidemia, gout, and hypertension. Fine-mapping and trans-Omics analyses with gene expression in 47 tissues and plasma protein levels implicate genes potentially operating through differential expression in kidney (including TGFB1, MUC1, PRKCI, and OAF), and allow coupling of UACR associations to altered plasma OAF concentrations. Knockdown of OAF and PRKCI orthologs in Drosophila nephrocytes reduces albumin endocytosis. Silencing fly PRKCI further impairs slit diaphragm formation. These results generate a priority list of genes and pathways for translational research to reduce albuminuria., Competing interests: Karsten B. Sieber is full-time employee of GlaxoSmithKline. Gardar Sveinbjornsson, Daniel F. Gudbjartsson, Hilma Holm, Unnur Thorsteinsdottir and Kari Stefansson are full-time employees of deCODE genetics, Amgen Inc. John Danesh is member of the Novartis Cardiovascular and Metabolic Advisory Board, received grant support from Novartis. Oscar H. Franco works in ErasmusAGE, a center for aging research across the life course funded by Nestlé Nutrition (Nestec Ltd.), Metagenics Inc., and AXA. Wolfgang Koenig received modest consultation fees for advisory board meetings from Amgen, DalCor, Kowa, Novartis, Pfizer and Sanofi, and modest personal fees for lectures from Amgen, AstraZeneca, Novartis, Pfizer and Sanofi. Anna I. Podgornaia and Dermot F. Reilly are employees of Merck Sharp Dohme Corp., Whitehouse Station, NJ, USA. Kevin Ho disclosed a research and financial relationship with Sanofi-Genzyme. Bruce M. Psaty serves on the DSMB of a clinical trial funded by the manufacturer (Zoll LifeCor) and on the Steering Committee of the Yale Open Data Access Project funded by Johnson & Johnson. Markus Scholz: Consultancy of and grant support from Merck Serono not related to this project. Adam S. Butterworth received grants from MSD, Pfizer, Novartis, Biogen and Bioverativ and personal fees from Novartis. Anna Köttgen received grant support from Gruenenthal not related to this project. The other authors declare no competing interests.

Highlight The OsMSH4/OsMSH5 heterodimer interacts with type A and C RPA heterotrimer complexes during second-end capture to regulate crossing over during meiosis I in rice., Meiosis is essential for gametogenesis in sexual reproduction in rice (Oryza sativa L.). We identified a MutS-homolog (MSH) family gene OsMSH4 in a trisomic plant. Cytological analysis showed that developments of both pollen and embryo sacs in an Osmsh4 mutant were blocked due to defective chromosome pairing. Compared with the wild type, the Osmsh4 mutant displayed a significant ~21.9% reduction in chiasma frequency, which followed a Poisson distribution, suggesting that class I crossover formation in the mutant was impaired. Temporal and spatial expression pattern analyses showed that OsMSH4 was preferentially expressed in meiocytes during their meiosis, indicating a critical role in gametogenesis. Subcellular localization showed that OsMSH4–green fluorescent protein was predominantly located in the nucleus. OsMSH4 could interact with another MSH member (OsMSH5) through the N-terminus and C-terminus, respectively. Direct physical interaction between OsMSH5, OsRPA1a, OsRPA2b, OsRPA1c, and OsRPA2c was identified by yeast two-hybrid assays and further validated by pull-down assays. Our results supported the conclusion that the OsMSH4/5 heterodimer plays a key role in regulation of crossover formation during rice meiosis by interaction with the RPA complex.

Summary To enable direct comparison of ancestry background in different studies, we developed LASER to estimate individual ancestry by placing either sezquenced or genotyped samples in a common ancestry space, regardless of the sequencing strategy or genotyping array used to characterize each sample. Here we describe the LASER server to facilitate application of the method to a wide range of genetic studies. The server provides genetic ancestry estimation for different geographic regions and user-friendly interactive visualization of the results. Availability and Implementation The LASER server is freely accessible at http://laser.sph.umich.edu/ Supplementary information Supplementary data are available at Bioinformatics online.

Asian populations are currently underrepresented in human genetics research. Here we present whole-genome sequencing data of 4,810 Singaporeans from three diverse ethnic groups: 2,780 Chinese, 903 Malays, and 1,127 Indians. Despite a medium depth of 13.7×, we achieved essentially perfect (>99.8%) sensitivity and accuracy for detecting common variants and good sensitivity (>89%) for detecting extremely rare variants with 0.01) that were absent in the existing public databases, highlighting the importance of local population reference for genetic diagnosis. We describe fine-scale genetic structure of Singapore populations and their relationship to worldwide populations from the 1000 Genomes Project. In addition to revealing noticeable amounts of admixture among three Singapore populations and a Malay-related novel ancestry component that has not been captured by the 1000 Genomes Project, our analysis also identified some fine-scale features of genetic structure consistent with two waves of prehistoric migration from south China to Southeast Asia. Finally, we demonstrate that our data can substantially improve genotype imputation not only for Singapore populations, but also for populations across Asia and Oceania. These results highlight the genetic diversity in Singapore and the potential impacts of our data as a resource to empower human genetics discovery in a broad geographic region.

Obstructive sleep apnea (OSA) is a common heritable disorder displaying marked sexual dimorphism in disease prevalence and progression. Previous genetic association studies have identified a few genetic loci associated with OSA and related quantitative traits, but they have only focused on single ethnic groups, and a large proportion of the heritability remains unexplained. The apnea-hypopnea index (AHI) is a commonly used quantitative measure characterizing OSA severity. Because OSA differs by sex, and the pathophysiology of obstructive events differ in rapid eye movement (REM) and non-REM (NREM) sleep, we hypothesized that additional genetic association signals would be identified by analyzing the NREM/REM-specific AHI and by conducting sex-specific analyses in multiethnic samples. We performed genome-wide association tests for up to 19,733 participants of African, Asian, European, and Hispanic/Latino American ancestry in 7 studies. We identified rs12936587 on chromosome 17 as a possible quantitative trait locus for NREM AHI in men (N = 6,737; P = 1.7 × 10 -8 ) but not in women (P = 0.77). The association with NREM AHI was replicated in a physiological research study (N = 67; P = 0.047). This locus overlapping the RAI1 gene and encompassing genes PEMT1, SREBF1, and RASD1 was previously reported to be associated with coronary artery disease, lipid metabolism, and implicated in Potocki-Lupski syndrome and Smith-Magenis syndrome, which are characterized by abnormal sleep phenotypes. We also identified gene-by-sex interactions in suggestive association regions, suggesting that genetic variants for AHI appear to vary by sex, consistent with the clinical observations of strong sexual dimorphism.

Blood pressure (BP) is a major risk factor for cardiovascular disease and more than 200 genetic loci associated with BP are known. Here, we perform a multi-stage genome-wide association study for BP (max N = 289,038) principally in East Asians and meta-analysis in East Asians and Europeans. We report 19 new genetic loci and ancestry-specific BP variants, conforming to a common ancestry-specific variant association model. At 10 unique loci, distinct non-rare ancestry-specific variants colocalize within the same linkage disequilibrium block despite the significantly discordant effects for the proxy shared variants between the ethnic groups. The genome-wide transethnic correlation of causal-variant effect-sizes is 0.898 and 0.851 for systolic and diastolic BP, respectively. Some of the ancestry-specific association signals are also influenced by a selective sweep. Our results provide new evidence for the role of common ancestry-specific variants and natural selection in ethnic differences in complex traits such as BP., Blood pressure (BP) is a major risk factor for cardiovascular disease and more than 200 genetic loci associated with BP are known. Here, the authors perform discovery GWAS for BP in East Asians and meta-analysis in East Asians and Europeans and report ancestry-specific BP SNPs and selection signals.

With advances in Whole Genome Sequencing (WGS) technology, more advanced statistical methods for testing genetic association with rare variants are being developed. Methods in which variants are grouped for analysis are also known as variant-set, gene-based, and aggregate unit tests. The burden test and Sequence Kernel Association Test (SKAT) are two widely used variant-set tests, which were originally developed for samples of unrelated individuals and later have been extended to family data with known pedigree structures. However, computationally-efficient and powerful variant-set tests are needed to make analyses tractable in large-scale WGS studies with complex study samples. In this paper, we propose the variant-Set Mixed Model Association Tests (SMMAT) for continuous and binary traits using the generalized linear mixed model framework. These tests can be applied to large-scale WGS studies involving samples with population structure and relatedness, such as in the National Heart, Lung, and Blood Institute’s Trans-Omics for Precision Medicine (TOPMed) program. SMMAT tests share the same null model for different variant sets, and a virtue of this null model, which includes covariates only, is that it needs to be only fit once for all tests in each genome-wide analysis. Simulation studies show that all the proposed SMMAT tests correctly control type I error rates for both continuous and binary traits in the presence of population structure and relatedness. We also illustrate our tests in a real data example of analysis of plasma fibrinogen levels in the TOPMed program (n = 23,763), using the Analysis Commons, a cloud-based computing platform.

We consider in this article testing rare variants by environment interactions in sequencing association studies. Current methods for studying the association of rare variants with traits cannot be readily applied for testing for rare variants by environment interactions, as these methods do not effectively control for the main effects of rare variants, leading to unstable results and/or inflated Type 1 error rates. We will first analytically study the bias of the use of conventional burden-based tests for rare variants by environment interactions, and show the tests can often be invalid and result in inflated Type 1 error rates. To overcome these difficulties, we develop the interaction sequence kernel association test (iSKAT) for assessing rare variants by environment interactions. The proposed test iSKAT is optimal in a class of variance component tests and is powerful and robust to the proportion of variants in a gene that interact with environment and the signs of the effects. This test properly controls for the main effects of the rare variants using weighted ridge regression while adjusting for covariates. We demonstrate the performance of iSKAT using simulation studies and illustrate its application by analysis of a candidate gene sequencing study of plasma adiponectin levels.

Accurate estimation of individual ancestry is important in genetic association studies, especially when a large number of samples are collected from multiple sources. However, existing approaches developed for genome-wide SNP data do not work well with modest amounts of genetic data, such as in targeted sequencing or exome chip genotyping experiments. We propose a statistical framework to estimate individual ancestry in a principal component ancestry map generated by a reference set of individuals. This framework extends and improves upon our previous method for estimating ancestry using low-coverage sequence reads (LASER 1.0) to analyze either genotyping or sequencing data. In particular, we introduce a projection Procrustes analysis approach that uses high-dimensional principal components to estimate ancestry in a low-dimensional reference space. Using extensive simulations and empirical data examples, we show that our new method (LASER 2.0), combined with genotype imputation on the reference individuals, can substantially outperform LASER 1.0 in estimating fine-scale genetic ancestry. Specifically, LASER 2.0 can accurately estimate fine-scale ancestry within Europe using either exome chip genotypes or targeted sequencing data with off-target coverage as low as 0.05×. Under the framework of LASER 2.0, we can estimate individual ancestry in a shared reference space for samples assayed at different loci or by different techniques. Therefore, our ancestry estimation method will accelerate discovery in disease association studies not only by helping model ancestry within individual studies but also by facilitating combined analysis of genetic data from multiple sources.

Knowledge of biological relatedness between samples is important for many genetic studies. In large-scale human genetic association studies, the estimated kinship is used to remove cryptic relatedness, control for family structure, and estimate trait heritability. However, estimation of kinship is challenging for sparse sequencing data, such as those from off-target regions in target sequencing studies, where genotypes are largely uncertain or missing. Existing methods often assume accurate genotypes at a large number of markers across the genome. We show that these methods, without accounting for the genotype uncertainty in sparse sequencing data, can yield a strong downward bias in kinship estimation. We develop a computationally efficient method called SEEKIN to estimate kinship for both homogeneous samples and heterogeneous samples with population structure and admixture. Our method models genotype uncertainty and leverages linkage disequilibrium through imputation. We test SEEKIN on a whole exome sequencing dataset (WES) of Singapore Chinese and Malays, which involves substantial population structure and admixture. We show that SEEKIN can accurately estimate kinship coefficient and classify genetic relatedness using off-target sequencing data down sampled to ~0.15X depth. In application to the full WES dataset without down sampling, SEEKIN also outperforms existing methods by properly analyzing shallow off-target data (~0.75X). Using both simulated and real phenotypes, we further illustrate how our method improves estimation of trait heritability for WES studies., Author summary Inference of genetic relatedness from molecular markers has broad applications in many areas, including quantitative genetics, forensics, evolution and ecology. Classic estimators, however, are not suitable for low-coverage sequencing data, which have high levels of genotype uncertainty and missing data. We evaluate existing methods and describe a new method for kinship estimation using sparse sequencing data. Our method leverages correlations between neighboring markers and models genotype uncertainty in kinship estimators for both homogeneous populations and admixed populations. We show that our method can accurately estimate kinship coefficient even when the sequencing depth is as low as ~0.15X, while existing methods have strong downward bias. Our method can be applied to estimate kinship using sparse off-target data and thus enables control of family structure and estimation of heritability in target sequencing studies, in which the deeply sequenced target regions are often too small to infer genetic relatedness. Even for whole exome sequencing, we show that our method can improve kinship and heritability estimation by including off-target data, compared to conventional analyses solely based on the target regions.

The stratified scatterplots show how the effect of Pb on Mental and Motor Composite Score is modified by the number of minor alleles at the two top SNPs. In particular, we can see how both scores appear to fall as Pb increases for subjects with no minor alleles (black symbols), but scores appear to rise as Pb increases for subjects with one minor alleles (blue symbols). This trend occurs for both SNPs and both outcomes, showing the significant interaction effect between the two SNPs and Pb concentration. (DOCX 169 kb)

Q-Q plots of GWIS. (DOCX 9 mb)

Manhattan plots displaying genetic effects from genome-wide association of meta-analysis on mental or motor composite scores. (DOCX 5 mb)

Spatial and temporal expression trajectories of top genes associated with neurodevelopmental outcomes. (DOCX 1 mb)

Underrepresentation of Asian genomes has hindered population and medical genetics research on Asians, leading to population disparities in precision medicine. By whole-genome sequencing of 4,810 Singapore Chinese, Malays, and Indians, we found 98.3 million SNPs and small insertions or deletions, over half of which are novel. Population structure analysis demonstrated great representation of Asian genetic diversity by three ethnicities in Singapore and revealed a Malay-related novel ancestry component. Furthermore, demographic inference suggested that Malays split from Chinese ∼24,800 years ago and experienced significant admixture with East Asians ∼1,700 years ago, coinciding with the Austronesian expansion. Additionally, we identified 20 candidate loci for natural selection, 14 of which harbored robust associations with complex traits and diseases. Finally, we show that our data can substantially improve genotype imputation in diverse Asian and Oceanian populations. These results highlight the value of our data as a resource to empower human genetics discovery across broad geographic regions. Agency for Science, Technology and Research (A*STAR) National Medical Research Council (NMRC) National Research Foundation (NRF) Accepted version We acknowledge H.M. Kang, S. Das, A. Tan, F. Zhang, J. Terhorst, P.-R. Loh, and G. Hellenthal for helpful discussions and support from all participants and clinical research coordinators of the contributing cohorts and studies: the TTSH Healthy Control Workgroup, the SEED cohort, the Asian Sudden Cardiac Death in Heart Failure Study, the Singapore Heart Failure Outcomes and Phenotypes (SHOP) cohort, the Asian neTwork for Translational Research and Cardiovascular Trials (ATTRaCT), the Parkinson’s Disease Study, the Peranakan Genome Study, the Platinum Asian Genomes Project, the Bariatric Surgery Study, the National Heart Centre Singapore Biobank and SingHEART cohorts, and the GUSTO and S-PRESTO study groups. This study was supported by Singapore’s A*STAR (core funding and IAF-PP H17/01/a0/007), BMRC (SPF2014/001, SPF2013/002, SPF2014/003, SPF2014/004, and SPF2014/005), NMRC (CIRG/1371/2013, CIRG/1417/2015, CIRG/1488/ 2018, CSA-SI/0012/2017, CG/017/2013, CG/M006/2017_NHCS, TCR/013- NNI/2014, STaR/0011/2012, STaR2013/001, STaR/014/2013, STaR/0026/ 2015, TCR/006-NUHS/2013, TCR/012-NUHS/2014, TCR/004-NUS/2008, TCR/012-NUHS/2014, and center grants 2010-13 and 2013-2017), NRF (NRFF2016-03), National University of Singapore, SingHealth and DukeNUS, and Alexandra Health small innovative grant SIGII/15203 and funding from Huazhong University of Science and Technology, the Tanoto Foundation, the Lee Foundation, the Boston Scientific Investigator Sponsored Research Program and Bayer, the NSF (DEB-1753489), and the Alfred P. Sloan Foundation. The computation was partially performed on resources of the National Supercomputing Centre, Singapore (https://www.nscc.sg).