Interfacial Domino Effect Triggered by ß-alanine Cations Realized Highly Reversible Zinc-Metal Anodes.

Realizing durative dense, dendrite-free, and no by-product deposition configuration on Zn anodes is crucial to solving the short circuit and premature failure of batteries, which is simultaneously determined by the Zn interface chemistry, electro-reduction kinetics, mass transfer process, and their interaction. Herein, this work unmasks a domino effect of the ß-alanine cations (Ala+) within the hydrogel matrix, which effectively triggers the subsequent electrostatic shielding and beneficial knock-on effects via the specifical adsorption earliest event on the Zn anode surface. The electrostatic shielding effect regulates the crystallographic energetic preference of Zn deposits and retards fast electro-reduction kinetics, thereby steering stacked stockier block morphology and realizing crystallographic optimization. Meanwhile, the mass transfer rate of Zn2+ ions was accelerated via the SO42- anion immobilized caused by Ala+ in bulk electrolyte, finally bringing the balance between electroreduction kinetics and mass transfer process, which enables dendrite-free Zn deposition behavior. Concomitantly, the interfacial adsorbed Ala+ cations facilitate the electrochemical reduction of interfacial SO42- anions to form the inorganic-organic hybrid solid electrolyte interphase layer. The above domino effects immensely improve the utilization efficiency of Zn anodes and long-term stability, as demonstrated by the 12 times longer life of Zn||Zn cells (3650 h) and ultrahigh Coulombic efficiency (99.4%).

De novo and somatic structural variant discovery with SVision-pro.

Long-read-based de novo and somatic structural variant (SV) discovery remains challenging, necessitating genomic comparison between samples. We developed SVision-pro, a neural-network-based instance segmentation framework that represents genome-to-genome-level sequencing differences visually and discovers SV comparatively between genomes without any prerequisite for inference models. SVision-pro outperforms state-of-the-art approaches, in particular, the resolving of complex SVs is improved, with low Mendelian error rates, high sensitivity of low-frequency SVs and reduced false-positive rates compared with SV merging approaches.

Haplotype-resolved assemblies and variant benchmark of a Chinese Quartet.

BACKGROUND: Recent state-of-the-art sequencing technologies enable the investigation of challenging regions in the human genome and expand the scope of variant benchmarking datasets. Herein, we sequence a Chinese Quartet, comprising two monozygotic twin daughters and their biological parents, using four short and long sequencing platforms (Illumina, BGI, PacBio, and Oxford Nanopore Technology). RESULTS: The long reads from the monozygotic twin daughters are phased into paternal and maternal haplotypes using the parent-child genetic map and for each haplotype. We also use long reads to generate haplotype-resolved whole-genome assemblies with completeness and continuity exceeding that of GRCh38. Using this Quartet, we comprehensively catalogue the human variant landscape, generating a dataset of 3,962,453 SNVs, 886,648 indels (< 50 bp), 9726 large deletions (≥ 50 bp), 15,600 large insertions (≥ 50 bp), 40 inversions, 31 complex structural variants, and 68 de novo mutations which are shared between the monozygotic twin daughters. Variants underrepresented in previous benchmarks owing to their complexity-including those located at long repeat regions, complex structural variants, and de novo mutations-are systematically examined in this study. CONCLUSIONS: In summary, this study provides high-quality haplotype-resolved assemblies and a comprehensive set of benchmarking resources for two Chinese monozygotic twin samples which, relative to existing benchmarks, offers expanded genomic coverage and insight into complex variant categories.

Comparison and benchmark of structural variants detected from long read and long-read assembly.

Structural variant (SV) detection is essential for genomic studies, and long-read sequencing technologies have advanced our capacity to detect SVs directly from read or de novo assembly, also known as read-based and assembly-based strategy. However, to date, no independent studies have compared and benchmarked the two strategies. Here, on the basis of SVs detected by 20 read-based and eight assembly-based detection pipelines from six datasets of HG002 genome, we investigated the factors that influence the two strategies and assessed their performance with well-curated SVs. We found that up to 80% of the SVs could be detected by both strategies among different long-read datasets, whereas variant type, size, and breakpoint detected by read-based strategy were greatly affected by aligners. For the high-confident insertions and deletions at non-tandem repeat regions, a remarkable subset of them (82% in assembly-based calls and 93% in read-based calls), accounting for around 4000 SVs, could be captured by both reads and assemblies. However, discordance between two strategies was largely caused by complex SVs and inversions, which resulted from inconsistent alignment of reads and assemblies at these loci. Finally, benchmarking with SVs at medically relevant genes, the recall of read-based strategy reached 77% on 5X coverage data, whereas assembly-based strategy required 20X coverage data to achieve similar performance. Therefore, integrating SVs from read and assembly is suggested for general-purpose detection because of inconsistently detected complex SVs and inversions, whereas assembly-based strategy is optional for applications with limited resources.

Evaluation of Pericardial Thickening and Adhesion Using High-Frequency Ultrasound.

BACKGROUND: Routine echocardiography using a standard-frequency ultrasound probe has insufficient spatial resolution to clearly visualize the parietal pericardium (PP). High-frequency ultrasound (HFU) has enhanced axial resolution. The aim of this study was to use a commercially available high-frequency linear probe to evaluate apical PP thickness (PPT) and pericardial adhesion in both normal pericardium and pericardial diseases. METHODS: From April 2002 to March 2022, 227 healthy individuals, 205 patients with apical aneurysm (AA) and 80 patients with chronic constrictive pericarditis (CP) were recruited to participate in this study. All subjects underwent both standard-frequency ultrasound and HFU to image the apical PP (APP) and pericardial adhesion. Some subjects underwent computed tomography (CT). RESULTS: Apical PPT was measured using HFU and found to be 0.60 ± 0.01 mm (0.37-0.87 mm) in normal control subjects, 1.22 ± 0.04 mm (0.48-4.53 mm) in patients with AA, and 2.91 ± 0.17 mm (1.13-9.01 mm) in patients with CP. Tiny physiologic effusions were observed in 39.2% of normal individuals. Pericardial adhesion was detected in 69.8% of patients with local pericarditis due to AA and 97.5% of patients with CP. Visibly thickened visceral pericardium was observed in six patients with CP. Apical PPT measurements obtained by HFU correlated well with those obtained by CT in those patients with CP. However, CT could clearly visualize the APP in only 45% of normal individuals and 37% of patients with AA. In 10 patients with CP, both HFU and CT demonstrated equal ability to visualize the very thickened APP. CONCLUSIONS: Apical PPT measured using HFU in normal control subjects ranged from 0.37 to 0.87 mm, consistent with previous reports from necropsy studies. HFU had higher resolution in distinguishing local pericarditis of the AA from normal individuals. HFU was superior to CT in imaging APP lesions, as CT failed to visualize the APP in more than half of both normal individuals and patients with AA. The fact that all 80 patients with CP in our study had significantly thickened APP raises doubt regarding the previously reported finding that 18% of patients with CP had normal PPT.

SVision: a deep learning approach to resolve complex structural variants.

Complex structural variants (CSVs) encompass multiple breakpoints and are often missed or misinterpreted. We developed SVision, a deep-learning-based multi-object-recognition framework, to automatically detect and haracterize CSVs from long-read sequencing data. SVision outperforms current callers at identifying the internal structure of complex events and has revealed 80 high-quality CSVs with 25 distinct structures from an individual genome. SVision directly detects CSVs without matching known structures, allowing sensitive detection of both common and previously uncharacterized complex rearrangements.

Mako: A Graph-based Pattern Growth Approach to Detect Complex Structural Variants.

Complex structural variants (CSVs) are genomic alterations that have more than two breakpoints and are considered as the simultaneous occurrence of simple structural variants. However, detecting the compounded mutational signals of CSVs is challenging through a commonly used model-match strategy. As a result, there has been limited progress for CSV discovery compared with simple structural variants. Here, we systematically analyzed the multi-breakpoint connection feature of CSVs, and proposed Mako, utilizing a bottom-up guided model-free strategy, to detect CSVs from paired-end short-read sequencing. Specifically, we implemented a graph-based pattern growth approach, where the graph depicts potential breakpoint connections, and pattern growth enables CSV detection without pre-defined models. Comprehensive evaluations on both simulated and real datasets revealed that Mako outperformed other algorithms. Notably, validation rates of CSVs on real data based on experimental and computational validations as well as manual inspections are around 70%, where the medians of experimental and computational breakpoint shift are 13 bp and 26 bp, respectively. Moreover, the Mako CSV subgraph effectively characterized the breakpoint connections of a CSV event and uncovered a total of 15 CSV types, including two novel types of adjacent segment swap and tandem dispersed duplication. Further analysis of these CSVs also revealed the impact of sequence homology on the formation of CSVs. Mako is publicly available at https://github.com/xjtu-omics/Mako.

Case report: Multiple biventricular aneurysms in arrhythmogenic cardiomyopathy.

Arrhythmogenic cardiomyopathy (ACM) is a genetic disease characterized by fibro-fatty myocardial replacement and is clinically associated with malignant ventricular arrhythmias and sudden cardiac death. It presents a major diagnostic and therapeutic challenge due to its complex clinical presentation and multiparametric diagnostic scoring system that includes structural, histological, and electrocardiographic data. A 57-year-old man with a history of palpitation and premature ventricular contractions (PVC) experienced syncope and sustained ventricular tachycardia at a rate of 213 bpm, which was successfully rescued by synchronized cardioversion. Multiple ventricular aneurysms were found in the right ventricular free wall and the left ventricular apical regions, as well as mild biventricular systolic dysfunction, according to echocardiography and high-frequency ultrasound. The genetic analysis revealed the following desmoplakin genes, chr6-7585274-7585275, NM_004415, exon24, and c.7780delT (p.S2594Pfs*9), a heterozygous and likely pathogenic mutation, as the mutation sites in the patient and his 24-year-old daughter. During the 21-month follow-up, the patient did not experience syncope or pre-syncope symptoms while on ß-blocker (bisoprolol) therapy. Among the multimodality imaging techniques of the ACM, late gadolinium enhancement on cardiac magnetic resonance (CMR) is accepted as a more objective indicator of myocardial fibrosis. Left ventricular systolic dysfunction, fibrosis on CMR, and frequent PVC are the primary and most sensitive clinical signs of desmoplakin cardiomyopathy. However, echocardiography continues to be the most commonly used imaging modality for assessing focal ventricular movement and structural abnormalities. The pathological characteristics of arrhythmogenic cardiomyopathy of the right ventricular anterior free wall and apical regions near the transducer can be better shown using high-frequency linear ultrasound with a higher resolution.

Three chromosome-scale Papaver genomes reveal punctuated patchwork evolution of the morphinan and noscapine biosynthesis pathway.

For millions of years, plants evolve plenty of structurally diverse secondary metabolites (SM) to support their sessile lifestyles through continuous biochemical pathway innovation. While new genes commonly drive the evolution of plant SM pathway, how a full biosynthetic pathway evolves remains poorly understood. The evolution of pathway involves recruiting new genes along the reaction cascade forwardly, backwardly, or in a patchwork manner. With three chromosome-scale Papaver genome assemblies, we here reveal whole-genome duplications (WGDs) apparently accelerate chromosomal rearrangements with a nonrandom distribution towards SM optimization. A burst of structural variants involving fusions, translocations and duplications within 7.7 million years have assembled nine genes into the benzylisoquinoline alkaloids gene cluster, following a punctuated patchwork model. Biosynthetic gene copies and their total expression matter to morphinan production. Our results demonstrate how new genes have been recruited from a WGD-induced repertoire of unregulated enzymes with promiscuous reactivities to innovate efficient metabolic pathways with spatiotemporal constraint.

Haplotype-resolved diverse human genomes and integrated analysis of structural variation.

Long-read and strand-specific sequencing technologies together facilitate the de novo assembly of high-quality haplotype-resolved human genomes without parent-child trio data. We present 64 assembled haplotypes from 32 diverse human genomes. These highly contiguous haplotype assemblies (average minimum contig length needed to cover 50% of the genome: 26 million base pairs) integrate all forms of genetic variation, even across complex loci. We identified 107,590 structural variants (SVs), of which 68% were not discovered with short-read sequencing, and 278 SV hotspots (spanning megabases of gene-rich sequence). We characterized 130 of the most active mobile element source elements and found that 63% of all SVs arise through homology-mediated mechanisms. This resource enables reliable graph-based genotyping from short reads of up to 50,340 SVs, resulting in the identification of 1526 expression quantitative trait loci as well as SV candidates for adaptive selection within the human population.

Fabrication of superhydrophilic PVDF membranes by one-step modification with eco-friendly phytic acid and polyethyleneimine complex for oil-in-water emulsions separation.

Superhydrophilic membranes with simultaneous underwater superoleophobicity are highly desirable and worth exploring for separation of emulsified oil from water. In this work, combining the strong negative charges of phytic acid (PA) and the high cationic charge density of polyethyleneimine (PEI), an eco-friendly PA@PEI polyelectrolyte complex was synthetized in aqueous solution. And then the polyelectrolyte complex was deposited onto hydrophobic PVDF membranes through a one-step assembly approach with high convenience, endowing the membranes with superhydrophilic and underwater superoleophobic property. The as-prepared PA@PEI/PVDF membrane shows outstanding static and dynamic water stability, and was successfully used to separate multiple oil-in-water emulsions, with an average rejection rate exceeding 98.5% and a water flux up to 12203.6 L m-2∙h-1∙bar-1. Furthermore, the water flux can be recovered to a high level after four separation-washing cycles, showing excellent antifouling performance and recovery capability. Together with its natural raw materials and environmentally friendly preparation strategy, the PA@PEI/PVDF membrane shows great potential in practical treatment of emulsified oily wastewater.

MSIsensor-pro: Fast, Accurate, and Matched-normal-sample-free Detection of Microsatellite Instability.

Microsatellite instability (MSI) is a key biomarker for cancer therapy and prognosis. Traditional experimental assays are laborious and time-consuming, and next-generation sequencing-based computational methods do not work on leukemia samples, paraffin-embedded samples, or patient-derived xenografts/organoids, due to the requirement of matched normal samples. Herein, we developed MSIsensor-pro, an open-source single sample MSI scoring method for research and clinical applications. MSIsensor-pro introduces a multinomial distribution model to quantify polymerase slippages for each tumor sample and a discriminative site selection method to enable MSI detection without matched normal samples. We demonstrate that MSIsensor-pro is an ultrafast, accurate, and robust MSI calling method. Using samples with various sequencing depths and tumor purities, MSIsensor-pro significantly outperformed the current leading methods in both accuracy and computational cost. MSIsensor-pro is available at https://github.com/xjtu-omics/msisensor-pro and free for non-commercial use, while a commercial license is provided upon request.

MEpurity: estimating tumor purity using DNA methylation data.

MOTIVATION: Tumor purity is a fundamental property of each cancer sample and affects downstream investigations. Current tumor purity estimation methods either require matched normal sample or report moderately high tumor purity even on normal samples. It is critical to develop a novel computational approach to estimate tumor purity with sufficient precision based on tumor-only sample. RESULTS: In this study, we developed MEpurity, a beta mixture model-based algorithm, to estimate the tumor purity based on tumor-only Illumina Infinium 450k methylation microarray data. We applied MEpurity to both The Cancer Genome Atlas (TCGA) cancer data and cancer cell line data, demonstrating that MEpurity reports low tumor purity on normal samples and comparable results on tumor samples with other state-of-art methods. AVAILABILITY AND IMPLEMENTATION: MEpurity is a C++ program which is available at https://github.com/xjtu-omics/MEpurity. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PVTree: A Sequential Pattern Mining Method for Alignment Independent Phylogeny Reconstruction.

Phylogenetic tree is essential to understand evolution and it is usually constructed through multiple sequence alignment, which suffers from heavy computational burdens and requires sophisticated parameter tuning. Recently, alignment free methods based on k-mer profiles or common substrings provide alternative ways to construct phylogenetic trees. However, most of these methods ignore the global similarities between sequences or some specific valuable features, e.g., frequent patterns overall datasets. To make further improvement, we propose an alignment free algorithm based on sequential pattern mining, where each sequence is converted into a binary representation of sequential patterns among sequences. The phylogenetic tree is further constructed via clustering distance matrix which is calculated from pattern vectors. To increase accuracy for highly divergent sequences, we consider pattern weight and filtering redundancy sub-patterns. Both simulated and real data demonstrates our method outperform other alignment free methods, especially for large sequence set with low similarity.