Vaccine Molecule Design Based on Phage Display and Computational Modeling against Rhabdovirus.

Rhabdoviruses with rich species lead a variety of high lethality and rapid transmission diseases to plants and animals around the globe. Vaccination is one of the most effective approaches to prevent and control virus disease. However, the key antigenic epitopes of glycoprotein being used for vaccine development are unclear. In this study, fish-derived Abs are employed for a Micropterus salmoides rhabdovirus (MSRV) vaccine design by phage display and bioinformatics analysis. We constructed an anti-MSRV phage Ab library to screen Abs for glycoprotein segment 2 (G2) (G129-266). Four M13-phage-displayed Abs (Ab-5, Ab-7, Ab-8 and Ab-30) exhibited strong specificity to target Ag, and Ab-7 had the highest affinity with MSRV. Ab-7 (300 µg/ml) significantly increased grass carp ovary cell viability to 83.40% and significantly decreased the titer of MSRV. Molecular docking results showed that the key region of Ag-Ab interaction was located in 10ESQEFTTLTSH20 of G2. G2Ser11 and G2Gln12 were replaced with alanine, respectively, and molecular docking results showed that the Ag-Ab was nonbinding (ΔG > 0). Then, the peptide vaccine KLH-G210-20 was immunized to M. salmoides via i.p. injection. ELISA result showed that the serum Ab potency level increased significantly (p < 0.01). More importantly, the challenge test demonstrated that the peptide vaccine elicited robust protection against MSRV invasion, and the relative percentage survival reached 62.07%. Overall, this study proposed an approach for screening key epitope by combining phage display technology and bioinformatics tools to provide a reliable theoretical reference for the prevention and control of viral diseases.

A flexible empirical Bayes approach to multivariate multiple regression, and its improved accuracy in predicting multi-tissue gene expression from genotypes.

Predicting phenotypes from genotypes is a fundamental task in quantitative genetics. With technological advances, it is now possible to measure multiple phenotypes in large samples. Multiple phenotypes can share their genetic component; therefore, modeling these phenotypes jointly may improve prediction accuracy by leveraging effects that are shared across phenotypes. However, effects can be shared across phenotypes in a variety of ways, so computationally efficient statistical methods are needed that can accurately and flexibly capture patterns of effect sharing. Here, we describe new Bayesian multivariate, multiple regression methods that, by using flexible priors, are able to model and adapt to different patterns of effect sharing and specificity across phenotypes. Simulation results show that these new methods are fast and improve prediction accuracy compared with existing methods in a wide range of settings where effects are shared. Further, in settings where effects are not shared, our methods still perform competitively with state-of-the-art methods. In real data analyses of expression data in the Genotype Tissue Expression (GTEx) project, our methods improve prediction performance on average for all tissues, with the greatest gains in tissues where effects are strongly shared, and in the tissues with smaller sample sizes. While we use gene expression prediction to illustrate our methods, the methods are generally applicable to any multi-phenotype applications, including prediction of polygenic scores and breeding values. Thus, our methods have the potential to provide improvements across fields and organisms.

xQTLbiolinks: a comprehensive and scalable tool for integrative analysis of molecular QTLs.

Genome-wide association studies (GWAS) have identified thousands of disease-associated non-coding variants, posing urgent needs for functional interpretation. Molecular Quantitative Trait Loci (xQTLs) such as eQTLs serve as an essential intermediate link between these non-coding variants and disease phenotypes and have been widely used to discover disease-risk genes from many population-scale studies. However, mining and analyzing the xQTLs data presents several significant bioinformatics challenges, particularly when it comes to integration with GWAS data. Here, we developed xQTLbiolinks as the first comprehensive and scalable tool for bulk and single-cell xQTLs data retrieval, quality control and pre-processing from public repositories and our integrated resource. In addition, xQTLbiolinks provided a robust colocalization module through integration with GWAS summary statistics. The result generated by xQTLbiolinks can be flexibly visualized or stored in standard R objects that can easily be integrated with other R packages and custom pipelines. We applied xQTLbiolinks to cancer GWAS summary statistics as case studies and demonstrated its robust utility and reproducibility. xQTLbiolinks will profoundly accelerate the interpretation of disease-associated variants, thus promoting a better understanding of disease etiologies. xQTLbiolinks is available at https://github.com/lilab-bioinfo/xQTLbiolinks.

Fine-mapping from summary data with the "Sum of Single Effects" model.

In recent work, Wang et al introduced the "Sum of Single Effects" (SuSiE) model, and showed that it provides a simple and efficient approach to fine-mapping genetic variants from individual-level data. Here we present new methods for fitting the SuSiE model to summary data, for example to single-SNP z-scores from an association study and linkage disequilibrium (LD) values estimated from a suitable reference panel. To develop these new methods, we first describe a simple, generic strategy for extending any individual-level data method to deal with summary data. The key idea is to replace the usual regression likelihood with an analogous likelihood based on summary data. We show that existing fine-mapping methods such as FINEMAP and CAVIAR also (implicitly) use this strategy, but in different ways, and so this provides a common framework for understanding different methods for fine-mapping. We investigate other common practical issues in fine-mapping with summary data, including problems caused by inconsistencies between the z-scores and LD estimates, and we develop diagnostics to identify these inconsistencies. We also present a new refinement procedure that improves model fits in some data sets, and hence improves overall reliability of the SuSiE fine-mapping results. Detailed evaluations of fine-mapping methods in a range of simulated data sets show that SuSiE applied to summary data is competitive, in both speed and accuracy, with the best available fine-mapping methods for summary data.

Robots as models of evolving systems.

Experimental robobiological physics can bring insights into biological evolution. We present a development of hybrid analog/digital autonomous robots with mutable diploid dominant/recessive 6-byte genomes. The robots are capable of death, rebirth, and breeding. We map the quasi-steady-state surviving local density of the robots onto a multidimensional abstract "survival landscape." We show that robot death in complex, self-adaptive stress landscapes proceeds by a general lowering of the robotic genetic diversity, and that stochastically changing landscapes are the most difficult to survive.

Cauchy hyper-graph Laplacian nonnegative matrix factorization for single-cell RNA-sequencing data analysis.

Many important biological facts have been found as single-cell RNA sequencing (scRNA-seq) technology has advanced. With the use of this technology, it is now possible to investigate the connections among individual cells, genes, and illnesses. For the analysis of single-cell data, clustering is frequently used. Nevertheless, biological data usually contain a large amount of noise data, and traditional clustering methods are sensitive to noise. However, acquiring higher-order spatial information from the data alone is insufficient. As a result, getting trustworthy clustering findings is challenging. We propose the Cauchy hyper-graph Laplacian non-negative matrix factorization (CHLNMF) as a unique approach to address these issues. In CHLNMF, we replace the measurement based on Euclidean distance in the conventional non-negative matrix factorization (NMF), which can lessen the influence of noise, with the Cauchy loss function (CLF). The model also incorporates the hyper-graph constraint, which takes into account the high-order link among the samples. The CHLNMF model's best solution is then discovered using a half-quadratic optimization approach. Finally, using seven scRNA-seq datasets, we contrast the CHLNMF technique with the other nine top methods. The validity of our technique was established by analysis of the experimental outcomes.

Monomethylation and -protonation of Lutetium Dinitrogen Complex.

Due to the highly chemically inert nature, direct activation and transformation of dinitrogen are challenging. Here, we disclose the synthesis, isolation, and derivatization of (N2)3- supported by lutetium complex. Initially, a (N2)3- radical, in [{(C5Me5){MeC(NiPr)2}Lu}2(µ2-η2:η2-N2)][K(crypt)] (crypt = 2,2,2-cryptand) complex, was generated through the reduction of neutral lutetium dinitrogen complex [{(C5Me5){MeC(NiPr)2}Lu}2(µ2-η2:η2-N2)] with potassium metal. Subsequently, the reaction of (N2)3- complex with methyl triflate (or triflic acid) led to the formation of an N-C (or N-H) bond, yielding the corresponding [{(C5Me5){MeC(NiPr)2}Lu}2(NN-R)(OTf)][K(crypt)] (R = Me, H, OTf = CF3SO3) as the product. Both electron paramagnetic resonance spectroscopy and density functional theory analyses support the radical character of the NN-Me unit. The Lu-N bonds in the (NN-Me)•2- radical complex are predominantly ionic, with 77% of the unpaired electron localized on the (NN-Me) fragment. Moreover, the geometry of the pure organic radical (NN-Me)•2-, optimized by double-hybrid density functional theory, closely matches that of the (NN-Me)•2- lutetium complex.

Biosynthesis of Enfumafungin-type Antibiotic Reveals an Unusual Enzymatic Fusion Pattern and Unprecedented C-C Bond Cleavage.

Enfumafungin-type antibiotics, represented by enfumafungin and fuscoatroside, belong to a distinct group of triterpenoids derived from fungi. These compounds exhibit significant antifungal properties with ibrexafungerp, a semisynthetic derivative of enfumafungin, recently gaining FDA's approval as the first oral antifungal drug for treating invasive vulvar candidiasis. Enfumafungin-type antibiotics possess a cleaved E-ring with an oxidized carboxyl group and a reduced methyl group at the break site, suggesting unprecedented C-C bond cleavage chemistry involved in their biosynthesis. Here, we show that a 4-gene (fsoA, fsoD, fsoE, fsoF) biosynthetic gene cluster is sufficient to yield fuscoatroside by heterologous expression in Aspergillus oryzae. Notably, FsoA is an unheard-of terpene cyclase-glycosyltransferase fusion enzyme, affording a triterpene glycoside product that relies on enzymatic fusion. FsoE is a P450 enzyme that catalyzes successive oxidation reactions at C19 to facilitate a C-C bond cleavage, producing an oxidized carboxyl group and a reduced methyl group that have never been observed in known P450 enzymes. Our study thus sets the important foundation for the manufacture of enfumafungin-type antibiotics using biosynthetic approaches.

Biosynthesis of fungal terpenoids.

Covering: up to August 2023Terpenoids, which are widely distributed in animals, plants, and microorganisms, are a large group of natural products with diverse structures and various biological activities. They have made great contributions to human health as therapeutic agents, such as the anti-cancer drug paclitaxel and anti-malarial agent artemisinin. Accordingly, the biosynthesis of this important class of natural products has been extensively studied, which generally involves two major steps: hydrocarbon skeleton construction by terpenoid cyclases and skeleton modification by tailoring enzymes. Additionally, fungi (Ascomycota and Basidiomycota) serve as an important source for the discovery of terpenoids. With the rapid development of sequencing technology and bioinformatics approaches, genome mining has emerged as one of the most effective strategies to discover novel terpenoids from fungi. To date, numerous terpenoid cyclases, including typical class I and class II terpenoid cyclases as well as emerging UbiA-type terpenoid cyclases, have been identified, together with a variety of tailoring enzymes, including cytochrome P450 enzymes, flavin-dependent monooxygenases, and acyltransferases. In this review, our aim is to comprehensively present all fungal terpenoid cyclases identified up to August 2023, with a focus on newly discovered terpenoid cyclases, especially the emerging UbiA-type terpenoid cyclases, and their related tailoring enzymes from 2015 to August 2023.

Regulatory variants in TCF7L2 are associated with thoracic aortic aneurysm.

Thoracic aortic aneurysm (TAA) is characterized by dilation of the aortic root or ascending/descending aorta. TAA is a heritable disease that can be potentially life threatening. While 10%-20% of TAA cases are caused by rare, pathogenic variants in single genes, the origin of the majority of TAA cases remains unknown. A previous study implicated common variants in FBN1 with TAA disease risk. Here, we report a genome-wide scan of 1,351 TAA-affected individuals and 18,295 control individuals from the Cardiovascular Health Improvement Project and Michigan Genomics Initiative at the University of Michigan. We identified a genome-wide significant association with TAA for variants within the third intron of TCF7L2 following replication with meta-analysis of four additional independent cohorts. Common variants in this locus are the strongest known genetic risk factor for type 2 diabetes. Although evidence indicates the presence of different causal variants for TAA and type 2 diabetes at this locus, we observed an opposite direction of effect. The genetic association for TAA colocalizes with an aortic eQTL of TCF7L2, suggesting a functional relationship. These analyses predict an association of higher expression of TCF7L2 with TAA disease risk. In vitro, we show that upregulation of TCF7L2 is associated with BCL2 repression promoting vascular smooth muscle cell apoptosis, a key driver of TAA disease.

Dinitrogen Activation and Functionalization Affording Chromium Diazenido and Hydrazido Complexes.

ConspectusThe activation and functionalization of N2 to form nitrogen-element bonds have long posed challenges to industrial, biological, and synthetic chemists. The first transition-metal dinitrogen complex prepared by Allen and Senoff in 1965 provoked researchers to explore homogeneous N2 fixation. Despite intensive research in the last six decades, efficient and quantitative conversion of N2 to diazenido and hydrazido species remains problematic. Relative to a plethora of reactions to generate N2 complexes, their functionalization reactions are rather rare, and the yields are often unsatisfactory, emphasizing the need for systematic investigations of the reaction mechanisms.In this Account, we summarize our recent work on the synthesis, spectroscopic features, electronic structures, and reactivities of several Cr-N2 complexes. Initially, a series of dinuclear and trinuclear Cr(I)-N2 complexes bearing cyclopentadienyl-phosphine ligands were accessed. However, they cannot achieve N2 functionalization but undergo oxidative addition reactions with phenylsilane, azobenzene, and other unsaturated organic compounds at the low-valent Cr(I) centers rather than at the N2 unit. Further reduction of these Cr(I) complexes leads to the formation of more activated mononuclear Cr(0) bis-dinitrogen complexes. Remarkably, silylation of the cyclopentadienyl-phosphine Cr(0)-N2 complex with Me3SiCl afforded the first Cr hydrazido complex. This process follows the distal pathway to functionalize the Nß atom twice, yielding an end-on η1-hydrazido complex, Cr(III)═N-N(SiMe3)2. In contrast, upon substitution of the phosphine ligand in the Cr(0)-N2 complex with a N-heterocyclic carbene (NHC) ligand, the corresponding reaction with Me3SiCl proceeds via the alternating pathway; the silylation occurs at both Nα and Nß atoms and generates a side-on η2-hydrazido complex, Cr(III)(η2-Me3SiN-NSiMe3). Both silylation reactions are inevitably accompanied by the formation of Cr(III) hydrazido complexes and Cr(II) chlorides with a 2:1 ratio. These processes exhibit a peculiar '3-4-2-1' stoichiometry (i.e., treating 3 equiv of Cr(0)-N2 complexes with 4 equiv of Me3SiCl yields 2 equiv of Cr(III) disilyl-hydrazido complexes and 1 equiv of Cr(II) chloride). Upon replacing the monodentate phosphine and/or NHC ligand with a bisphosphine ligand, a monodinitrogen Cr(0) complex, instead of the bis-dinitrogen Cr(0) complexes, is obtained; consequently, the silylation reactions progress via the normal two-electron route, which passes through Cr(II)-N═N-R diazenido species as an intermediate and furnishes [Cr(IV)═N-NR2]+ hydrazido as the final products. More importantly, this type of Cr(0)-N2 complex can be not only silylated but also protonated and alkylated proficiently. All of the second-order reaction rates of the first and second transformations are determined along with the lifetimes of the intervening diazenido species. Based on these findings, we have successfully carried out nearly quantitative preparations of the Cr(IV) hydrazido species with unmixed or hybrid substituents.The studies of Cr-N2 systems provide effective approaches for the activation and functionalization of N2, deepening the understanding of N2 electrophilic attack. We hope that this Account will inspire more discoveries related to the transformation of gaseous N2 to high-value-added nitrogen-containing organic compounds.

Systemic neutrophils are triggered by respiratory Bacillus Calmette- Guérin and mediate pulmonary mycobacterial clearance in synergy with the triggering receptor expressed on myeloid cells 1.

Tuberculosis remains a threat to public health. The only approved vaccine, Bacillus Calmette-Guérin (BCG), is administered intradermally and provides limited protection, and its effect on innate immunity via the respiratory route has not been fully elucidated. A mouse model with genetically depleted TREM1 and seven-color flow cytometry staining were used to characterize the comprehensive immune response induced by respiratory BCG, through evaluating organ bacterial loads, lung histopathology, and lung immunohistochemistry. During respiratory BCG infection, the murine lungs displayed effective bacterial clearance. Notably, marked differences in neutrophils were observed between thymus and bone marrow cells, characterized by a significant increase in the expression of the triggering receptor expressed on myeloid cells 1 (TREM1). Subsequently, upon depletion of TREM1, a reduction in pulmonary neutrophils was observed, which further exacerbated bacterial loads and resulted in worsened pathology following respiratory BCG infection. In summary, up-regulated expression of TREM1 in rapidly increasing circulating neutrophil by pulmonary BCG is required for an efficient host response to BCG infection, and suggests the important role of TREM1 in neutrophil-related pulmonary bacteria clearance and pathology.

Prognostic value of pre-treatment [18F] FDG PET/CT in recurrent nasopharyngeal carcinoma without distant metastasis.

BACKGROUND: [18 F]-Fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) has the ability to detect local and/or regional recurrence as well as distant metastasis. We aimed to evaluate the prognosis value of PET/CT in locoregional recurrent nasopharyngeal (lrNPC). METHODS: A total of 451 eligible patients diagnosed with recurrent I-IVA (rI-IVA) NPC between April 2009 and December 2015 were retrospectively included in this study. The differences in overall survival (OS) of lrNPC patients with and without PET/CT were compared in the I-II, III-IVA, r0-II, and rIII-IVA cohorts, which were grouped by initial staging and recurrent staging (according to MRI). RESULTS: In the III-IVA and rIII-IVA NPC patients, with PET/CT exhibited significantly higher OS rates in the univariate analysis (P = 0.045; P = 0.009; respectively). Multivariate analysis revealed that with PET/CT was an independent predictor of OS in the rIII-IVA cohort (hazard ratio [HR] = 0.476; 95% confidence interval [CI]: 0.267 to 0.847; P = 0.012). In the rIII-IVA NPC, patients receiving PET/CT sacns before salvage surgery had a better prognosis compared with MRI alone (P = 0.036). The recurrent stage (based on PET/CT) was an independent predictor of OS. (r0-II versus [vs]. rIII-IVA; HR = 0.376; 95% CI: 0.150 to 0.938; P = 0.036). CONCLUSION: The present study showed that with PET/CT could improve overall survival for rIII-IVA NPC patients. PET/CT appears to be an effective method for assessing rTNM staging.

Catechol compounds as dual-targeting agents for fish protection against Ichthyophthirius multifiliis infections.

Aquaculture is one of the fastest growing sectors in global food production, recognized as a significant contributor to poverty alleviation, food security, and income generation. However, the frequent occurrence of diseases caused by pathogen infections result in reduced yields and economic losses, posing a substantial constraint to the sustainable development of aquaculture. Here, our study identified that four catechol compounds, quercetin, luteolin, caffeic acid, and chlorogenic acid, exhibited potent antiparasitic effects against Ichthyophthirius multifiliis in both, in vitro and in vivo. The parasite is recognized as one of the most pathogenic to fish worldwide. Using a combination of in silico methods, the dipeptidyl peptidase (DPP) was identified as a critical target for catechol compounds. The two hydroxyl radicals of the catechol group were essential for its binding to and interacting with the DPP protein. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses indicated that catechol compounds disrupt pathways associated with the metabolism and growth of I. multifiliis, thereby exerting antiparasitic effects. Furthermore, these compounds attenuated the expression of proinflammatory cytokines in vivo in fish and promoted macrophage polarization toward M2 phenotype by inhibiting the STAT1 signaling pathway. The dual activity of catechol compounds, acting as both direct antiparasitic and anti-inflammatory agents in fish, offers a promising therapeutic approach for combating I. multifiliis infections in aquaculture.

Absolute Configuration of Oxabornyl Polyenes Prugosenes A1-A3 and Structural Revision of Prugosene A2.

Oxabornyl polyenes represent a unique group of polyketides characterized by a central polyene core flanked by a conserved oxabornyl moiety and a structurally diverse oxygen heterocyclic ring. They are widely distributed in fungi and possess a variety of biological activities. Due to the significant spatial separation between the two stereogenic ring systems, it is difficult to establish their overall relative configurations. Here, we isolated three oxabornyl polyenes, prugosenes A1-A3 (1-3), from Talaromyces sp. JNU18266-01. Although these compounds were first reported from Penicillium rugulosum, their overall relative and absolute configurations remained unassigned. By employing ozonolysis in combination with ECD calculations, we were able to establish their absolute configurations, and additionally obtained seven new chemical derivatives (4-10). Notably, through NMR data analysis and quantum chemical calculations, we achieved the structural revision of prugosene A2. Furthermore, prugosenes A1-A3 exhibited potent antiviral activity against the respiratory syncytial virus, with compound 1 displaying an IC50 value of 6.3 µM. Our study thus provides a valuable reference for absolute configuration assignment of oxabornyl polyene compounds.

Lonicerin promotes wound healing in diabetic rats by enhancing blood vessel regeneration through Sirt1-mediated autophagy.

Among the numerous complications of diabetes mellitus, diabetic wounds seriously affect patients' quality of life and result in considerable psychological distress. Promoting blood vessel regeneration in wounds is a crucial step in wound healing. Lonicerin (LCR), a bioactive compound found in plants of the Lonicera japonica species and other honeysuckle plants, exhibits anti-inflammatory and antioxidant activities, and it recently has been found to alleviate ulcerative colitis by enhancing autophagy. In this study we investigated the efficacy of LCR in treatment of diabetic wounds and the underlying mechanisms. By comparing the single-cell transcriptomic data from healing and non-healing states in diabetic foot ulcers (DFU) of 5 patients, we found that autophagy and SIRT signaling activation played a crucial role in mitigating inflammation and oxidative stress, and promoting cell survival in wound healing processes. In TBHP-treated human umbilical vein endothelial cells (HUVECs), we showed that LCR alleviated cell apoptosis, and enhanced the cell viability, migration and angiogenesis. Furthermore, we demonstrated that LCR treatment dose-dependently promoted autophagy in TBHP-treated HUVECs by upregulating Sirt1 expression, and exerted its anti-apoptotic effect through the Sirt1-autophagy axis. Knockdown of Sirt1 significantly decreased the level of autophagy, and mitigated the anti-apoptotic effect of LCR. In a STZ-induced diabetic rat model, administration of LCR significantly promoted wound healing, which was significantly attenuated by Sirt1 knockdown. This study highlights the potential of LCR as a therapeutic agent for the treatment of diabetic wounds and provides insights into the molecular mechanisms underlying its effects.

Analyzing the photoassociation spectrum of ultracold 85Rb 133Cs molecule in (3)3Σ+ state.

We establish a theoretical model to analyze the photoassociative spectroscopy of 85Rb 133Cs molecules in the (3)3Σ+ state. The vibrational energy, spin-spin coupling constant, and hyperfine interaction constant of the (3)3Σ+ state are determined based on nine observed vibrational levels. Consequently, the Rydberg-Klein-Rees potential energy curve of the (3)3Σ+ state is obtained and compared with the ab initial potential energy curve. Our model can be adopted to analyze the photoassociative spectroscopy of other heteronuclear alkali-metal diatomic molecules in the (3)3Σ+ state.

Unusual Electronic Structures of an Electron Transfer Series of [Cr(µ-η1 : η1 -N2 )Cr]0/1+/2.

In dinitrogen (N2 ) fixation chemistry, bimetallic end-on bridging N2 complexes M(µ-η1 : η1 -N2 )M can split N2 into terminal nitrides and hence attract great attention. To date, only 4d and 5d transition complexes, but none of 3d counterparts, could realize such a transformation. Likewise, complexes {[Cp*Cr(dmpe)]2 (µ-N2 )}0/1+/2+ (1-3) are incapable to cleave N2 , in contrast to their Mo congeners. Remarkably, cross this series the N-N bond length of the N2 ligand and the N-N stretching frequency exhibit unprecedented nonmonotonic variations, and complexes 1 and 2 in both solid and solution states display rare thermally activated ligand-mediated two-center spin transitions, distinct from discrete dinuclear spin crossovers. In-depth analyses using wave function based ab initio calculations reveal that the Cr-N2 -Cr bonding in complexes 1-3 is distinguished by strong multireference character and cannot be described by solely one electron configuration or Lewis structure, and that all intriguing spectroscopic observations originate in their sophisticate multireference electronic structures. More critical is that such multireference bonding of complexes 1-3 is at least a key factor that contributes to their kinetic inertness toward N2 splitting. The mechanistic understanding is then used to rationalize the disparate reactivity of related 3d M(µ-η1 : η1 -N2 )M complexes compared to their 4d and 5d analogs.

ERStruct: a fast Python package for inferring the number of top principal components from whole genome sequencing data.

BACKGROUND: Large-scale multi-ethnic DNA sequencing data is increasingly available owing to decreasing cost of modern sequencing technologies. Inference of the population structure with such sequencing data is fundamentally important. However, the ultra-dimensionality and complicated linkage disequilibrium patterns across the whole genome make it challenging to infer population structure using traditional principal component analysis based methods and software. RESULTS: We present the ERStruct Python Package, which enables the inference of population structure using whole-genome sequencing data. By leveraging parallel computing and GPU acceleration, our package achieves significant improvements in the speed of matrix operations for large-scale data. Additionally, our package features adaptive data splitting capabilities to facilitate computation on GPUs with limited memory. CONCLUSION: Our Python package ERStruct is an efficient and user-friendly tool for estimating the number of top informative principal components that capture population structure from whole genome sequencing data.

Comparison of multiple imputation and other methods for the analysis of imputed genotypes.

BACKGROUND: Analysis of imputed genotypes is an important and routine component of genome-wide association studies and the increasing size of imputation reference panels has facilitated the ability to impute and test low-frequency variants for associations. In the context of genotype imputation, the true genotype is unknown and genotypes are inferred with uncertainty using statistical models. Here, we present a novel method for integrating imputation uncertainty into statistical association tests using a fully conditional multiple imputation (MI) approach which is implemented using the Substantive Model Compatible Fully Conditional Specification (SMCFCS). We compared the performance of this method to an unconditional MI and two additional approaches that have been shown to demonstrate excellent performance: regression with dosages and a mixture of regression models (MRM). RESULTS: Our simulations considered a range of allele frequencies and imputation qualities based on data from the UK Biobank. We found that the unconditional MI was computationally costly and overly conservative across a wide range of settings. Analyzing data with Dosage, MRM, or MI SMCFCS resulted in greater power, including for low frequency variants, compared to unconditional MI while effectively controlling type I error rates. MRM andl MI SMCFCS are both more computationally intensive then using Dosage. CONCLUSIONS: The unconditional MI approach for association testing is overly conservative and we do not recommend its use in the context of imputed genotypes. Given its performance, speed, and ease of implementation, we recommend using Dosage for imputed genotypes with MAF [Formula: see text] 0.001 and Rsq [Formula: see text] 0.3.