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In the emerging field of laser-driven inertial confinement fusion, Joule heating generated via electromagnetic heating of the metal frame is a critical issue. However, there are few reported models explaining thermal damage to the aluminum alloy. The aim of this study was to build a coupled model for electromagnetic radiation and heat conversion of an ultrashort laser pulse on an aluminum alloy based on Ohm's law. Additionally, the application SiO2 films on aluminum alloy to improve the laser-induced damage threshold (LIDT) were simulated, and the effects of metal impurities in the aluminum alloy were analyzed. A model examining the relation between electromagnetic radiation and heat for a nanosecond laser irradiating an aluminum alloy was developed using a coupled model equation. The results obtained using the finite difference time domain (FDTD) algorithm can provide a theoretical basis for future improvement of the aluminum alloy LIDT.

Tourette syndrome (TS) is a childhood-onset neuropsychiatric disorder characterized by repetitive motor movements and vocal tics. The clinical manifestations of TS are complex and often overlap with other neuropsychiatric disorders. TS is highly heritable; however, the underlying genetic basis and molecular and neuronal mechanisms of TS remain largely unknown. We performed whole-exome sequencing of a hundred trios (probands and their parents) with detailed records of their clinical presentations and identified a risk gene, ASH1L, that was both de novo mutated and associated with TS based on a transmission disequilibrium test. As a replication, we performed follow-up targeted sequencing of ASH1L in additional 524 unrelated TS samples and replicated the association (P value = 0.001). The point mutations in ASH1L cause defects in its enzymatic activity. Therefore, we established a transgenic mouse line and performed an array of anatomical, behavioral, and functional assays to investigate ASH1L function. The Ash1l+/− mice manifested tic-like behaviors and compulsive behaviors that could be rescued by the tic-relieving drug haloperidol. We also found that Ash1l disruption leads to hyper-activation and elevated dopamine-releasing events in the dorsal striatum, all of which could explain the neural mechanisms for the behavioral abnormalities in mice. Taken together, our results provide compelling evidence that ASH1L is a TS risk gene.

To assess the clinical performance of an expanded noninvasive prenatal screening (NIPS) test (“NIPS-Plus”) for detection of both aneuploidy and genome-wide microdeletion/microduplication syndromes (MMS). A total of 94,085 women with a singleton pregnancy were prospectively enrolled in the study. The cell-free plasma DNA was directly sequenced without intermediate amplification and fetal abnormalities identified using an improved copy-number variation (CNV) calling algorithm. A total of 1128 pregnancies (1.2%) were scored positive for clinically significant fetal chromosome abnormalities. This comprised 965 aneuploidies (1.026%) and 163 (0.174%) MMS. From follow-up tests, the positive predictive values (PPVs) for T21, T18, T13, rare trisomies, and sex chromosome aneuploidies were calculated as 95%, 82%, 46%, 29%, and 47%, respectively. For known MMS (n = 32), PPVs were 93% (DiGeorge), 68% (22q11.22 microduplication), 75% (Prader–Willi/Angleman), and 50% (Cri du Chat). For the remaining genome-wide MMS (n = 88), combined PPVs were 32% (CNVs ≥10 Mb) and 19% (CNVs

At the end of 2019, a novel coronavirus COVID‐19 broke out. Due to its high contagiousness, more than 74 million people have been infected worldwide. Automatic segmentation of the COVID‐19 lesion area in CT images is an effective auxiliary medical technology which can quantitatively diagnose and judge the severity of the disease. In this paper, a multi‐class COVID‐19 CT image segmentation network is proposed, which includes a pyramid attention module to extract multi‐scale contextual attention information, and a residual convolution module to improve the discriminative ability of the network. A wavelet edge loss function is also proposed to extract edge features of the lesion area to improve the segmentation accuracy. For the experiment, a dataset of 4369 CT slices is constructed, including three symptoms: ground glass opacities, interstitial infiltrates, and lung consolidation. The dice similarity coefficients of three symptoms of the model achieve 0.7704, 0.7900, 0.8241 respectively. The performance of the proposed network on public dataset COVID‐SemiSeg is also evaluated. The results demonstrate that this model outperforms other state‐of‐the‐art methods and can be a powerful tool to assist in the diagnosis of positive infection cases, and promote the development of intelligent technology in the medical field.

Since discovered in Hubei, China in December 2019, Corona Virus Disease 2019 named COVID-19 has lasted more than one year, and the number of new confirmed cases and confirmed deaths is still at a high level. COVID-19 is an infectious disease caused by SARS-CoV-2. Although RT-PCR is considered the gold standard for detection of COVID-19, CT plays an important role in the diagnosis and evaluation of the therapeutic effect of COVID-19. Diagnosis and localization of COVID-19 on CT images using deep learning can provide quantitative auxiliary information for doctors. This article proposes a novel network with multi-receptive field attention module to diagnose COVID-19 on CT images. This attention module includes three parts, a pyramid convolution module (PCM), a multi-receptive field spatial attention block (SAB), and a multi-receptive field channel attention block (CAB). The PCM can improve the diagnostic ability of the network for lesions of different sizes and shapes. The role of SAB and CAB is to focus the features extracted from the network on the lesion area to improve the ability of COVID-19 discrimination and localization. We verify the effectiveness of the proposed method on two datasets. The accuracy rate of 97.12%, specificity of 96.89%, and sensitivity of 97.21% are achieved by the proposed network on DTDB dataset provided by the Beijing Ditan Hospital Capital Medical University. Compared with other state-of-the-art attention modules, the proposed method achieves better result. As for the public COVID-19 SARS-CoV-2 dataset, 95.16% for accuracy, 95.6% for F1-score and 99.01% for AUC are obtained. The proposed network can effectively assist doctors in the diagnosis of COVID-19 CT images.

Background Current copy number variation (CNV) identification methods have rapidly become mature. However, the postdetection processes such as variant interpretation or reporting are inefficient. To overcome this situation, we developed REDBot as an automated software package for accurate and direct generation of clinical diagnostic reports for prenatal and products of conception (POC) samples. Methods We applied natural language process (NLP) methods for analyzing 30,235 in‐house historical clinical reports through active learning, and then, developed clinical knowledge bases, evidence‐based interpretation methods and reporting criteria to support the whole postdetection pipeline. Results Of the 30,235 reports, we obtained 37,175 CNV‐paragraph pairs. For these pairs, the active learning approaches achieved a 0.9466 average F1‐score in sentence classification. The overall accuracy for variant classification was 95.7%, 95.2%, and 100.0% in retrospective, prospective, and clinical utility experiments, respectively. Conclusion By integrating NLP methods in CNVs postdetection pipeline, REDBot is a robust and rapid tool with clinical utility for prenatal and POC diagnosis.

Nanocomposite multilayer TiBN coatings were prepared on Si (100) and 9Cr18Mo substrates using TiBN composite cathode plasma immersion ion implantation and deposition technique (PIIID). Synthesis of TiBN composite cathodes was conducted by powder metallurgy technology and the content of hexagonal boron nitride (h-BN) was changed from 8% to 40% (mass fraction). The as-deposited coatings were characterized by energy dispersive spectrometer (EDS), grazing incidence X-ray diffraction (GIXRD), Fourier Transform Infrared Spectroscopy (FTIR) and high resolution transmission electron microcopy (HRTEM). EDS results show that the B content of the coatings was varied from 3.71% to 13.84% (molar fraction) when the composition of the h-BN in the composited cathodes was changed from 8 % to 40% (mass fraction). GIXRD results reveal that the TiBN coatings with a B content of 8% has the main diffraction peak of TiN (200), (220) and (311), and these peaks disappear when the B content is increased. FTIR analysis of the multilayer coatings showed the presence of h-BN in all coatings. TEM images reveal that all coatings have the characteristics of self-forming nanocomposite multilayers, where the nanocomposites are composed of face-centered cubic TiN or h-BN nanocrystalline embedded in amorphous matrix. The tribological tests reveal that the TiBN coatings exhibit a marked decrease of coefficient at room temperature (~0.25). The improved properties were found to be derived from the comprehensiveness of the self-forming multilayers structure and the h-BN solid lubrication effects in the coatings.

Detailed characterization of chromosomal abnormalities, a common cause for congenital abnormalities and pregnancy loss, is critical for elucidating genes for human fetal development. Here, 2186 product of conception (POC) samples were tested for copy number variations (CNVs) at two clinical diagnostic centers using whole genome sequencing and high-resolution chromosomal microarray analysis. We developed a new gene discovery approach to predict potential developmental genes and identified 275 candidate genes from CNVs detected from both datasets. Based on Mouse Genome Informatics (MGI) and Zebrafish model organism database (ZFIN), 75% of identified genes could lead to developmental defects when mutated. Genes involved in embryonic development, gene transcription and regulation of biological processes were significantly enriched. Especially, transcription factors and gene families sharing specific protein domains predominated, which included known developmental genes such as HOX, NKX homeodomain genes and helix-loop-helix containing HAND2, NEUROG2 and NEUROD1 as well as potential novel developmental genes. We observed that developmental genes were denser in certain chromosomal regions, enabling identification of 31 potential genomic loci with clustered genes associated with development.

Whole-genome sequencing (WGS) allows for a comprehensive view of the sequence of the human genome. We present and apply integrated methodologic steps for interrogating WGS data to characterize the genetic architecture of 10 heart- and blood-related traits in a sample of 1,860 African Americans. In order to evaluate the contribution of regulatory and non-protein coding regions of the genome, we conducted aggregate tests of rare variation across the entire genomic landscape using a sliding window, complemented by an annotation-based assessment of the genome using predefined regulatory elements and within the first intron of all genes. These tests were performed treating all variants equally as well as with individual variants weighted by a measure of predicted functional consequence. Significant findings were assessed in 1,705 individuals of European ancestry. After these steps, we identified and replicated components of the genomic landscape significantly associated with heart- and blood-related traits. For two traits, lipoprotein(a) levels and neutrophil count, aggregate tests of low-frequency and rare variation were significantly associated across multiple motifs. For a third trait, cardiac troponin T, investigation of regulatory domains identified a locus on chromosome 9. These practical approaches for WGS analysis led to the identification of informative genomic regions and also showed that defined non-coding regions, such as first introns of genes and regulatory domains, are associated with important risk factor phenotypes. This study illustrates the tractable nature of WGS data and outlines an approach for characterizing the genetic architecture of complex traits.

Tourette syndrome (TS) is a childhood-onset neuropsychiatric disorder characterized by repetitive motor movements and vocal tics. The clinical manifestations of TS are complex and often overlap with other neuropsychiatric disorders. TS is highly heritable; however, the underlying genetic basis and molecular and neuronal mechanisms of TS remain largely unknown. We performed whole-exome sequencing of a hundred trios (probands and their parents) with detailed records of their clinical presentations and identified a risk gene, ASH1L, that was both de novo mutated and associated with TS based on a transmission disequilibrium test. As a replication, we performed follow-up targeted sequencing of ASH1L in additional 524 unrelated TS samples and replicated the association (P value = 0.001). The point mutations in ASH1L cause defects in its enzymatic activity. Therefore, we established a transgenic mouse line and performed an array of anatomical, behavioral, and functional assays to investigate ASH1L function. The Ash1l

Thermal problems are huge challenges for solid state lasers that are interested in high output power, cooling of the nonlinear optics is insufficient to completely solve the problem of thermally induced stress, as residual thermal stress remains after cooling, which is first proposed, to the best of our knowledge. In this paper a comprehensive model incorporating principles of thermodynamics, mechanics and optics is proposed, and it is used to study the residual thermal stress of a mounted KDP crystal after cooling process from mechanical perspective, along with the effects of the residual thermal stress on the second harmonic generation (SHG) efficiency of a high-average-power laser. Effects of the structural parameters of the mounting configuration of the KDP crystal on the residual thermal stress are characterized, as well as the SHG efficiency. The numerical results demonstrate the feasibility of solving the problems of residual thermal stress from the perspective on structural design of mounting configuration.

The microstructural evolution process of face-centered cubic Cu-30 wt%Zn, which has very low stacking fault (SF) energy of only 14 mJ/m 2 , processed by high-pressure torsion, was investigated using transmission electron microscopy. Results reveal that deformation SFs/twin boundaries and cell blocks play the key role in the grain refinement process from ultrafine grains to nano grains. Equiaxed coarse grains with grain sizes of several microns were refined to ultrafine grains through the formation of high density of SFs, twins and cell blocks. With the accumulation of high density of dislocations at SF/twin boundaries, the emission of secondary SFs/twins further refined grains and transformed ultrafine grains into equiaxed grains with grain size of several tens nanometers. The observed grain refinement mechanism is significantly different from those of materials with medium to high SF energies in which full dislocation activities play a key role for grain refinement.

Understanding the evolution of disease-associated mutations is fundamental to analyze pathogenetics of diseases. Mutation, recombination (by GC-biased gene conversion, gBGC), and selection have been known to shape the evolution of disease-associated mutations, but how these evolutionary forces work together is still an open question. In this study, we analyzed several human large-scale datasets (1000 Genomes, ESP6500, ExAC and ClinVar), and found that base-biased mutagenesis generates more GC→AT than AT→GC mutations, while gBGC promotes the fixation of AT→GC mutations to balance the impact of base-biased mutation on genome. Due to this effect of gBGC, purifying selection removes more deleterious AT→GC mutations than GC→AT from population, but many high-frequency (fixed and nearly fixed) deleterious AT→GC mutations are remained possibly due to high genetic load. As a special subset, disease-associated mutations follow this evolutionary rule, in which disease-associated GC→AT mutations are more enriched in rare mutations compared with AT→GC, while disease-associated AT→GC are more enriched in mutations with high frequency. Thus, we presented a base-biased evolutionary framework that explains the base-biased generation and accumulation of disease-associated mutations in human populations.

Aluminum alloys are widely applied in optical turrets after coating and super-finishing. Gold films prepared on aluminum alloy substrates via electron beam (e-beam) evaporation are considered to be effective way to realize close to total reflection of incident light. Here, we investigated the optimization of the reflectivity parameters of e-beam evaporated gold films; then, the influence of different deposition parameters on the surface quality, adhesive force and reflectivity (incident light in the 650–1700 nm range) of the film at −20, 25 and 60°C were systematically studied. The results demonstrated that the reflectivity and adhesion of the gold films both increased after high temperature holding and decreased slightly after low temperature holding. However, the surface morphology of the gold film did not change substantially. After holding at 60 and −20°C, the adhesive force decreased, which indicated that the adhesion strength between the reflective membrane and the substrate decreased.

Ultra-clean manufacturing is an indispensable key technology for inertial confinement fusion (ICF) to generate clean and sustainable energy, but the pollutants from laser-induced damage are a threat to ultra-clean manufacturing. Here we investigate the damage of black glass in a high laser fluence system, which refers to high fluence laser beams in fusion class laser systems. Results show a significant dependence of damage parameters on the laser pulse duration at 355 nm before and after surface treatment by SiO2 films, which include the laser-induced damage threshold (LIDT), morphology and depth. The simulation indicates that the LIDT of SiO2 films on black glass is improved obviously, which is 14.1 J/cm2, while that of normal black glass is 10.2 J/cm2. The presence of impurities will aggravate the damage of the thin films and pollutes the laser system. LIDT of SiO2 films containing impurities is only 3.6 J/cm2. The experiments show that the average LIDT of black glass is 9.54 J/cm2 while that of thin films with impurities is no more than 4.12 J/cm2. These salient results provide a new concept for the protection of absorbing stray light for ultra-clean manufacturing.

Authorsâ original file for figure 3

of Genetic diversity in India and the inference of Eurasian population expansion

Hemophilia A (HA) is an X-linked bleeding disorder caused by deleterious mutations in the coagulation factor VIII gene (F8). To date, F8 mutations have been documented predominantly in European subjects and in American subjects of European descent. Information on F8 variants in individuals of more diverse ethnic backgrounds is limited.To discover novel and rare F8 variants, and to characterize F8 variants in diverse population backgrounds.We analyzed 2535 subjects, including 26 different ethnicities, whose data were available from the 1000 Genomes Project (1000G) phase 3 dataset, for F8 variants and their potential functional impact.We identified 3030 single nucleotide variants, 31 short deletions and insertions (Indels) and a large, 497 kb, deletion. Among all variants, 86.4% were rare variants and 55.6% were novel. Eighteen variants previously associated with HA were found in our study. Most of these 'HA variants' were ethnic-specific with low allele frequency; however, one variant (p.M2257V) was present in 27% of African subjects. The p.E132D, p.T281A, p.A303V and p.D422H 'HA variants' were identified only in males. Twelve novel missense variants were predicted to be deleterious. The large deletion was discovered in eight female subjects without affecting F8 transcription and the transcription of genes on the X chromosome.Characterizing F8 in the 1000G project highlighted the complexity of F8 variants and the importance of interrogating genetic variants on multiple ethnic backgrounds for associations with bleeding and thrombosis. The haplotype analysis and the orientation of duplicons that flank the large deletion suggested that the deletion was recurrent and originated by homologous recombination.

INTRODUCTION A majority of imbalances in DNA methylation between homologous chromosomes in humans are sequence-dependent; the DNA sequence differences between the two chromosomes cause differences in the methylation state of neighboring cytosines on the same chromosome. The analyses of this sequence-dependent allele-specific methylation (SD-ASM) traditionally involved measurement of average methylation levels across many cells. Detailed understanding of SD-ASM at the single-cell and single-chromosome levels is lacking. This gap in understanding may hide the connection between SD-ASM, ubiquitous stochastic cell-to-cell and chromosome-to-chromosome variation in DNA methylation, and the puzzling and evolutionarily conserved patterns of intermediate methylation at gene regulatory loci. RATIONALE Whole-genome bisulfite sequencing (WGBS) provides the ultimate single-chromosome level of resolution and comprehensive whole-genome coverage required to explore SD-ASM. However, the exploration of the link between SD-ASM, stochastic variation in DNA methylation, and gene regulation requires deep coverage by WGBS across tissues and individuals and the context of other epigenomic marks and gene transcription. RESULTS We constructed maps of allelic imbalances in DNA methylation, histone marks, and gene transcription in 71 epigenomes from 36 distinct cell and tissue types from 13 donors. Deep (1691-fold) combined WGBS read coverage across 49 methylomes revealed CpG methylation imbalances exceeding 30% differences at 5% of the loci, which is more conservative than previous estimates in the 8 to 10% range; a similar value (8%) is observed in our dataset when we lowered our threshold for detecting allelic imbalance to 20% methylation difference between the two alleles. Extensive sequence-dependent CpG methylation imbalances were observed at thousands of heterozygous regulatory loci. Stochastic switching, defined as random transitions between fully methylated and unmethylated states of DNA, occurred at thousands of regulatory loci bound by transcription factors (TFs). Our results explain the conservation of intermediate methylation states at regulatory loci by showing that the intermediate methylation reflects the relative frequencies of fully methylated and fully unmethylated epialleles. SD-ASM is explainable by different relative frequencies of methylated and unmethylated epialleles for the two alleles. The differences in epiallele frequency spectra of the alleles at thousands of TF-bound regulatory loci correlated with the differences in alleles’ affinities for TF binding, which suggests a mechanistic explanation for SD-ASM. We observed an excess of rare variants among those showing SD-ASM, which suggests that an average human genome harbors at least ~200 detrimental rare variants that also show SD-ASM. The methylome’s sensitivity to genetic variation is unevenly distributed across the genome, which is consistent with buffering of housekeeping genes against the effects of random mutations. By contrast, less essential genes with tissue-specific expression patterns show sensitivity, thus providing opportunity for evolutionary innovation through changes in gene regulation. CONCLUSION Analysis of allelic epigenome maps provides a unifying model that links sequence-dependent allelic imbalances of the epigenome, stochastic switching at gene regulatory loci, selective buffering of the regulatory circuitry against the effects of random mutations, and disease-associated genetic variation.

Large-scale, population-based genomic studies have provided a context for modern medical genetics. Among such studies, however, African populations have remained relatively underrepresented. The breadth of genetic diversity across the African continent argues for an exploration of local genomic context to facilitate burgeoning disease mapping studies in Africa. We sought to characterize genetic variation and to assess population substructure within a cohort of HIV-positive children from Botswana—a Southern African country that is regionally underrepresented in genomic databases. Using whole-exome sequencing data from 164 Batswana and comparisons with 150 similarly sequenced HIV-positive Ugandan children, we found that 13%–25% of variation observed among Batswana was not captured by public databases. Uncaptured variants were significantly enriched (p = 2.2 × 10−16) for coding variants with minor allele frequencies between 1% and 5% and included predicted-damaging non-synonymous variants. Among variants found in public databases, corresponding allele frequencies varied widely, with Botswana having significantly higher allele frequencies among rare (

Introduction: The metabolome is a collection of small molecules in a biologic sample, and may serve as biomarkers or predictors of heart disease. Whole genome sequence analysis offers the opportunity to investigate rare and low-frequency annotated variants across the human genome. We used whole genome sequence analysis to characterize the genetic architecture of the serum metabolome. Methods: Whole genome sequencing and measurement (chromotagraphy and mass spectroscopy) of 245 serum metabolites were done in 1,458 European Americans and 1,679 African Americans from the Atherosclerosis Risk in Communities (ARIC) study, and these data were used to perform a trans-ethnic meta-analysis. Common variants (MAF>5%) were analyzed individually using an additive genetic model. Rare and low-frequency protein-altering variants (MAF≤5%) were aggregated by genes. In order to determine the contribution of regulatory and non-protein coding regions of the genome, we conducted aggregate tests across the entire genome using a 4kb sliding window as well as in predefined regulatory elements, which includs enhancers, promoter, and 3’ and 5’ untranslated region of a gene. Results: We identified 119 significant associations between genetic variants and metabolite levels (significance threshold p-10 for single variants, p-10 for aggregate tests), of which 49 were novel, including genes involved in known Mendelian conditions, protein biological processes, and disease related pathways. Six genes ( DMGDH, AGA, ACY1, PRODH, DDC and CPS1 ) causing rare inborn errors of metabolism were associated with amino acid levels in the general population. A predicated regulatory variant in the AGA gene, encoding a protein involved in asparagine generation, was associated with serum asparagine levels independent of any coding variants in this gene. Seven genes ( ABCC2, PKD2L1, SLC10A1, FDX1, CYP3A43, UGT2B15 and SULT2A1 ) related to lipid-related metabolite levels were identified, whose gene products are involved in secretion, channeling and transportation. Analysis of regulatory regions unraveled associations between three steroid lipids and a member of the cytochrome P450 family, CYP3A43 . Five genes within the kinin-kallikrein pathway were identified to be related to small peptide levels, including KLKB1 , KNG1 , F12 , ACE and CPN1 . Variants in CPN1 , which is known to bind to fibrinogen, were associated with DSGEGDFXAEGGGVR, a peptide which is produced during fibrinogen to fibrin conversion. Conclusion: This study outlines an approach to characterize the genetic architecture of the human serum metabolome and shows that sequence variants affect multiple human metabolites. Using the principle of Mendelian randomization, the next step is to determine whether any of these metabolites are in causal pathways to disease.

The radiation force of a high-energy laser caused by reflection at the input surface of a mounted KHsub2/subPOsub4/sub(KDP) crystal is studied, along with its effects on the second-harmonic generation (SHG) efficiency of the laser beam. A comprehensive model incorporating principles of momentum transfer, mechanics, and optics is proposed, taking advantage of which, the mechanical stress within the KDP crystal that is caused by the radiation force, and the SHG efficiency that is affected by the stress are successively studied. Moreover, the effects of the intensity of the laser beam on the radiation force, the stress, and the SHG efficiency are determined, respectively. It demonstrates that a high-energy laser beam causes macroscopic radiation force and further contributes negative effects to SHG efficiency.

In current work we perform molecular dynamics simulations to investigate the growth of Al thin film on Cu substrate through physical vapor deposition. The effects of incident angle on the morphology and the formed internal microstructures of Al thin films are emphasized. Simulation results show that Al thin films grow in the epitaxy growth mode of layer-by-layer fashion under incident energy of 0.1 eV. Further analysis of the internal microstructures demonstrates the formation of twin boundaries in Al thin films. It is found that the morphology of the island-like clusters formed in Al thin films varies significantly upon incident angle. The compositions of atoms of different lattice structures strongly depend on incident angle, which consequently affects the propensity of different internal microstructures formed in Al thin films.

Summary Background The von Willebrand factor (VWF) gene is highly polymorphic, with variants correlated with VWF antigen levels, adhesion activity, clearance and factor VIII binding. VWF mutations are detected in patients with von Willebrand disease (VWD), whereas polymorphic variants could be associated with thrombosis. However, information on the ethnic diversity of VWF variants and their association with diseases is limited. Objectives To characterize novel VWF variants from different ethnicities in the general population. Patients/Methods We analyzed samples from 1092 subjects of 14 ethnicities available in the 1000 Genomes database for VWF variants and their potential functional impacts. Results We identified 2728 SNPs and 91 insertions and deletions that had a high level of ethnic diversity, with Africans having the highest number of variants. The highest level of diversity was found in the D′ and D2 domains. Among 94 non-synonymous variants, 31 were predicted to be deleterious, including 19 that were previously associated with VWD. Most of these ‘VWD variants’ had allele frequencies consistent with disease incidence in European subjects, but some had a significantly higher frequency in other ethnicities. The mutations R2185Q, H817Q and M740I associated with type 1 and type 2N VWD were present in more than 13% of African subjects. Conclusions These results highlight the complexity of VWF variations in different ethnic groups and emphasize the importance of interrogating variations on multiple ethnic backgrounds for associations with bleeding and thrombosis.

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Next-generation sequencing is a powerful approach for discovering genetic variation. Sensitive variant calling and haplotype inference from population sequencing data remain challenging. We describe methods for high-quality discovery, genotyping, and phasing of SNPs for low-coverage (approximately 5×) sequencing of populations, implemented in a pipeline called SNPTools. Our pipeline contains several innovations that specifically address challenges caused by low-coverage population sequencing: (1) effective base depth (EBD), a nonparametric statistic that enables more accurate statistical modeling of sequencing data; (2) variance ratio scoring, a variance-based statistic that discovers polymorphic loci with high sensitivity and specificity; and (3) BAM-specific binomial mixture modeling (BBMM), a clustering algorithm that generates robust genotype likelihoods from heterogeneous sequencing data. Last, we develop an imputation engine that refines raw genotype likelihoods to produce high-quality phased genotypes/haplotypes. Designed for large population studies, SNPTools' input/output (I/O) and storage aware design leads to improved computing performance on large sequencing data sets. We apply SNPTools to the International 1000 Genomes Project (1000G) Phase 1 low-coverage data set and obtain genotyping accuracy comparable to that of SNP microarray.

Hardy Weinberg Equilibrium (HWE) test is widely used as a quality control measure to detect sequencing artifacts like mismapping, allelic dropout and biases. However, in the high throughput sequencing era, where the sample size is beyond a thousand scale, the utility of HWE test in reducing the false positive rate remains unclear. In this paper, we demonstrate that HWE test has limited power in identifying sequencing artifacts when the variant allele frequency is lower than 1% in a variant call set produced from more than five thousand whole genome sequenced samples from two homogeneous populations. We develop a novel strategy of implementing HWE filtering in which we incorporate site frequency spectrum information and determine the p-value cutoff which optimizes the tradeoff between sensitivity and specificity. The novel strategy is shown to outperform the exact test of HWE with an empirical constant p-value cutoff regardless of the sequencing sample size. We also present best practice recommendations for identifying possible sources of false positives from large sequencing datasets based on an analysis of intrinsic biases in the variant calling process. Our novel strategy of determining the HWE test p-value cutoff and applying the test to the common variants provides a practical approach for the variant level quality controls in the upcoming sequencing projects with tens to hundreds of thousand of samples.