TWAS Atlas: a curated knowledgebase of transcriptome-wide association studies.

Transcriptome-wide association studies (TWASs), as a practical and prevalent approach for detecting the associations between genetically regulated genes and traits, are now leading to a better understanding of the complex mechanisms of genetic variants in regulating various diseases and traits. Despite the ever-increasing TWAS outputs, there is still a lack of databases curating massive public TWAS information and knowledge. To fill this gap, here we present TWAS Atlas (https://ngdc.cncb.ac.cn/twas/), an integrated knowledgebase of TWAS findings manually curated from extensive literature. In the current implementation, TWAS Atlas collects 401,266 high-quality human gene-trait associations from 200 publications, covering 22,247 genes and 257 traits across 135 tissue types. In particular, an interactive knowledge graph of the collected gene-trait associations is constructed together with single nucleotide polymorphism (SNP)-gene associations to build up comprehensive regulatory networks at multi-omics levels. In addition, TWAS Atlas, as a user-friendly web interface, efficiently enables users to browse, search and download all association information, relevant research metadata and annotation information of interest. Taken together, TWAS Atlas is of great value for promoting the utility and availability of TWAS results in explaining the complex genetic basis as well as providing new insights for human health and disease research.

Self-Boosting Vaccination Based on Pulsatile Antigen Release from Core-Shell Microparticles.

Vaccination is among the most effective ways to prevent infectious diseases. Subunit vaccines are safe but usually require multiple booster shots, which may lead to immunity loss and economic consume. In this study, a self-boosting vaccine is developed based on the pulsatile release of antigen from the core-shell microparticle after single-injection immunization. Self-healing technology applied to form an "antigen core" can avoid organic solvents from destroying the spatial structure of the antigen. The "antigen shell" is built-up by self-assemble of the antigen with the opposite charged polypeptide. Primary immunization occurs with the self-assembled film disintegration, and the booster comes with the microparticle degradation. The changing of antigen-specific antibodies after immunization with the core-shell microparticle vaccine is consistent with that caused by the two shots of immunization. The immune effect and safety evaluation results support the translational potential of this self-boosting core-shell microparticle vaccine.

RefRGim: an intelligent reference panel reconstruction method for genotype imputation with convolutional neural networks.

Genotype imputation is a statistical method for estimating missing genotypes from a denser haplotype reference panel. Existing methods usually performed well on common variants, but they may not be ideal for low-frequency and rare variants. Previous studies showed that the population similarity between study and reference panels is one of the key factors influencing the imputation accuracy. Here, we developed an imputation reference panel reconstruction method (RefRGim) using convolutional neural networks (CNNs), which can generate a study-specified reference panel for each input data based on the genetic similarity of individuals from current study and references. The CNNs were pretrained with single nucleotide polymorphism data from the 1000 Genomes Project. Our evaluations showed that genotype imputation with RefRGim can achieve higher accuracies than original reference panel, especially for low-frequency and rare variants. RefRGim will serve as an efficient reference panel reconstruction method for genotype imputation. RefRGim is freely available via GitHub: https://github.com/shishuo16/RefRGim.

Strong Coupling Superconductivity in Ca-Intercalated Bilayer Graphene on SiC.

The metal-intercalated bilayer graphene has a flat band with a high density of states near the Fermi energy and thus is anticipated to exhibit an enhanced strong correlation effect and associated fascinating phenomena, including superconductivity. By using a self-developed multifunctional scanning tunneling microscope, we succeeded in observing the superconducting energy gap and diamagnetic response of a Ca-intercalated bilayer graphene below a critical temperature of 8.83 K. The revealed high value of gap ratio, 2Δ/kBTc ≈ 5.0, indicates a strong coupling superconductivity, while the variation of penetration depth with temperature and magnetic field indicates an isotropic s-wave superconductor. These results provide crucial experimental clues for understanding the origin and mechanism of superconductivity in carrier-doped graphene.

Precision Killing of Sinoporphyrin Sodium-Mediated Photodynamic Therapy against Malignant Tumor Cells.

Photodynamic therapy (PDT) has significant advantages in the treatment of malignant tumors, such as high efficiency, minimal invasion and less side effects, and it can preserve the integrity and quality of the organs. The power density, irradiation time and photosensitizer (PS) concentration are three main parameters that play important roles in killing tumor cells. However, until now, the underlying relationships among them for PDT outcomes have been unclear. In this study, human malignant glioblastoma U-118MG and melanoma A375 cells were selected, and the product of the power density, irradiation time and PS concentration was defined as the total photodynamic parameter (TPP), in order to investigate the mechanisms of PS sinoporphyrin sodium (DVDMS)-mediated PDT (DVDMS-PDT). The results showed that the survival rates of the U-118MG and A375 cells were negatively correlated with the TPP value in the curve, and the correlation exactly filed an e-exponential function. Moreover, according to the formula, we realized controllable killing effects of the tumor cells by randomly adjusting the three parameters, and we finally verified the accuracy and repeatability of the formula. In conclusion, the establishment and implementation of a newly functional relationship among the PDT parameters are essential for predicting PDT outcomes and providing personalized precise treatment, and they are contributive to the development of PDT dosimetry.

NucMap: a database of genome-wide nucleosome positioning map across species.

Dynamics of nucleosome positioning affects chromatin state, transcription and all other biological processes occurring on genomic DNA. While MNase-Seq has been used to depict nucleosome positioning map in eukaryote in the past years, nucleosome positioning data is increasing dramatically. To facilitate the usage of published data across studies, we developed a database named nucleosome positioning map (NucMap, http://bigd.big.ac.cn/nucmap). NucMap includes 798 experimental data from 477 samples across 15 species. With a series of functional modules, users can search profile of nucleosome positioning at the promoter region of each gene across all samples and make enrichment analysis on nucleosome positioning data in all genomic regions. Nucleosome browser was built to visualize the profiles of nucleosome positioning. Users can also visualize multiple sources of omics data with the nucleosome browser and make side-by-side comparisons. All processed data in the database are freely available. NucMap is the first comprehensive nucleosome positioning platform and it will serve as an important resource to facilitate the understanding of chromatin regulation.

Grain boundary engineering of Co3O4 nanomeshes for efficient electrochemical oxygen evolution.

The development of high-efficiency and stable electrocatalysts is significant for energy conversion and storage. The oxygen evolution reaction (OER), a pivotal half reaction, is seriously limited in its practical applications due to its sluggish kinetics and thus an excellent electrocatalyst for OER is urgently required. In this paper, we design a novel Co3O4 nanomesh (Co3O4 NMs) with high density grain boundaries (GBs), which functions as a highly efficient and steady OER electrocatalyst. The optimal Co3O4 NMs-500 can achieve a low overpotential of 295 mV at a current density of 10 mA cm-2, and a small Tafel slope of 31 mV dec-1, which exceeds the commercial Ir/C, as well as the majority of other catalysts reported in the literature. The Co3O4 NMs-500 also exhibit promising durability, with a negligible decline in activity after 18 h of operation. Detailed studies indicate that the presence of GBs leads to more exposed active sites and the enhanced adsorption of intermediate species on Co3O4 NMs-500, thereby improving the OER's catalytic activity. This work not only relates to the activity-GBs relationship, but also opens up a unique perspective for the design of the next generation of electrocatalysts.

Comprehensive Assessment of Genotype Imputation Performance.

Genotype imputation is a process of estimating missing ge-notypes from the haplotype or genotype reference panel. It can effectively boost the power of detecting single nucleotide polymorphisms (SNPs) in genome-wide association studies, integrate multi-studies for meta-analysis, and be applied in fine-mapping studies. The performance of genotype imputation is affected by many factors, including software, reference selection, sample size, and SNP density/sequencing coverage. A systematical evaluation of the imputation performance of current popular software will benefit future studies. Here, we evaluate imputation performances of Beagle4.1, IMPUTE2, MACH+Minimac3, and SHAPEIT2+ IM-PUTE2 using test samples of East Asian ancestry and references of the 1000 Genomes Project. The result indicated the accuracy of IMPUTE2 (99.18%) is slightly higher than that of the others (Beagle4.1: 98.94%, MACH+Minimac3: 98.51%, and SHAPEIT2+IMPUTE2: 99.08%). To achieve good and stable imputation quality, the minimum requirement of SNP density needs to be > 200/Mb. The imputation accuracies of IMPUTE2 and Beagle4.1 were under the minor influence of the study sample size. The contribution extent of reference to genotype imputation performance relied on software selection. We assessed the imputation performance on SNPs generated by next-generation whole genome sequencing and found that SNP sets detected by sequencing with 15× depth could be mostly got by imputing from the haplotype reference panel of the 1000 Genomes Project based on SNP data detected by sequencing with 4× depth. All of the imputation software had a weaker performance in low minor allele frequency SNP regions because of the bias of reference or software. In the future, more comprehensive reference panels or new algorithm developments may rise up to this challenge.

PGAP-X: extension on pan-genome analysis pipeline.

BACKGROUND: Since PGAP (pan-genome analysis pipeline) was published in 2012, it has been widely employed in bacterial genomics research. Though PGAP has integrated several modules for pan-genomics analysis, how to properly and effectively interpret and visualize the results data is still a challenge. RESULT: To well present bacterial genomic characteristics, a novel cross-platform software was developed, named PGAP-X. Four kinds of data analysis modules were developed and integrated: whole genome sequences alignment, orthologous genes clustering, pan-genome profile analysis, and genetic variants analysis. The results from these analyses can be directly visualized in PGAP-X. The modules for data visualization in PGAP-X include: comparison of genome structure, gene distribution by conservation, pan-genome profile curve and variation on genic and genomic region. Meanwhile, result data produced by other programs with similar function can be imported to be further analyzed and visualized in PGAP-X. To test the performance of PGAP-X, we comprehensively analyzed 14 Streptococcus pneumonia strains and 14 Chlamydia trachomatis. The results show that, S. pneumonia strains have higher diversity on genome structure and gene contents than C. trachomatis strains. In addition, S. pneumonia strains might have suffered many evolutionary events, such genomic rearrangements, frequent horizontal gene transfer, homologous recombination, and other evolutionary process. CONCLUSION: Briefly, PGAP-X directly presents the characteristics of bacterial genomic diversity with different visualization methods, which could help us to intuitively understand dynamics and evolution in bacterial genomes. The source code and the pre-complied executable programs are freely available from http://pgapx.ybzhao.com .

Surface Modification Progress for PLGA-Based Cell Scaffolds.

Poly(lactic-glycolic acid) (PLGA) is a biocompatible bio-scaffold material, but its own hydrophobic and electrically neutral surface limits its application as a cell scaffold. Polymer materials, mimics ECM materials, and organic material have often been used as coating materials for PLGA cell scaffolds to improve the poor cell adhesion of PLGA and enhance tissue adaptation. These coating materials can be modified on the PLGA surface via simple physical or chemical methods, and coating multiple materials can simultaneously confer different functions to the PLGA scaffold; not only does this ensure stronger cell adhesion but it also modulates cell behavior and function. This approach to coating could facilitate the production of more PLGA-based cell scaffolds. This review focuses on the PLGA surface-modified materials, methods, and applications, and will provide guidance for PLGA surface modification.

Genomic Characterization of a Carbapenem-Resistant Raoultella planticola Strain Co-Harboring blaIMP-4 and blaSHV-12 Genes.

Raoultella planticola is an emerging bacterial pathogen responsible for causing infections in both humans and animals. Unfortunately, sporadic reports of carbapenem-resistant R. planticola (CRRP) have been documented worldwide. Here we first reported the complete genome sequence of a CRRP isolate RP_3045 co-carrying blaIMP-4 and blaSHV-12, recovered from a patient in China, and its genetic relatedness to 82 R. planticola strains deposited in the NCBI GenBank database, sourced from humans, animals, and the environment. Whole-genome sequencing was performed using the Illumina NovaSeq 6000 and Oxford Nanopore MinION platforms. Phylogenetic analysis was also performed and visualized using a single nucleotide polymorphism (SNP)-based strategy. The complete genome of R. planticola strain RP_3045 was determined to be 6,312,961 bp in length, comprising five contigs that included one chromosome and four plasmids. RP_3045 was found to be multidrug-resistant and harbored several antimicrobial resistance genes, including both blaIMP-4 and blaSHV-12 genes located on a single plasmid. The most closely related strain was hkcpe63, recovered from humans in Hong Kong, China, in 2014, with 506 SNP differences. R. planticola strains were distributed globally and exhibited strong associations among isolates obtained from different sectors. This study provides evidence for the potential of R. planticola to disseminate carbapenem resistance across different sectors, highlighting the critical need for active and continuous surveillance of CRRP.

Monitoring the long-term spatiotemporal transmission dynamics and ecological surveillance of multidrug-resistant Salmonella enterica serovar Goldcoast: A multicenter genomic epidemiology study.

The emergence of multidrug-resistant Salmonella enterica serovar Goldcoast poses a significant threat to the effective treatment and control of salmonellosis within the ecological environment. Here, we conducted a genomic epidemiological study delineate the global dissemination scenarios of the multidrug-resistant S. Goldcoast originated from 11 countries for over 20 years. The population structure and evolutionary history of multidrug-resistant S. Goldcoast was investigated through phylogenomic and long-term spatiotemporal transmission dynamic analysis. ST358 and ST2529 are the predominant lineages of S. Goldcoast. Multidrug-resistant S. Goldcoast strains have mainly been identified in the ST358 lineage from human and the ST2529 lineage from livestock. ST358 S. Goldcoast was estimated to have emerged in the United Kingdom in 1969, and then spread to China, with both countries serve as centers for the global dissemination of the ST358 lineage. After its emergence and subsequent spread in Chinese clinical and environmental samples, occasional instances of this lineage have been reported in Canada, the United Kingdom, and Ireland. Clonal transmission of ST358 and ST2529 S. Goldcoast have occurred not only on an international and intercontinental scale but also among clinical, environmental and livestock samples. These data indicated that international circulation and local transmission of S. Goldcoast have occurred for over a decade. Continued surveillance of multidrug-resistant S. Goldcoast from a global "One Health" perspective is urgently needed to facilitate monitoring the spread of the antimicrobial resistant high-risk clones.

TM7SF3 controls TEAD1 splicing to prevent MASH-induced liver fibrosis.

The mechanisms of hepatic stellate cell (HSC) activation and the development of liver fibrosis are not fully understood. Here, we show that deletion of a nuclear seven transmembrane protein, TM7SF3, accelerates HSC activation in liver organoids, primary human HSCs, and in vivo in metabolic-dysfunction-associated steatohepatitis (MASH) mice, leading to activation of the fibrogenic program and HSC proliferation. Thus, TM7SF3 knockdown promotes alternative splicing of the Hippo pathway transcription factor, TEAD1, by inhibiting the splicing factor heterogeneous nuclear ribonucleoprotein U (hnRNPU). This results in the exclusion of the inhibitory exon 5, generating a more active form of TEAD1 and triggering HSC activation. Furthermore, inhibiting TEAD1 alternative splicing with a specific antisense oligomer (ASO) deactivates HSCs in vitro and reduces MASH diet-induced liver fibrosis. In conclusion, by inhibiting TEAD1 alternative splicing, TM7SF3 plays a pivotal role in mitigating HSC activation and the progression of MASH-related fibrosis.

Spike N354 glycosylation augments SARS-CoV-2 fitness for human adaptation through structural plasticity.

Selective pressures have given rise to a number of SARS-CoV-2 variants during the prolonged course of the COVID-19 pandemic. Recently evolved variants differ from ancestors in additional glycosylation within the spike protein receptor-binding domain (RBD). Details of how the acquisition of glycosylation impacts viral fitness and human adaptation are not clearly understood. Here, we dissected the role of N354-linked glycosylation, acquired by BA.2.86 sub-lineages, as a RBD conformational control element in attenuating viral infectivity. The reduced infectivity is recovered in the presence of heparin sulfate, which targets the 'N354 pocket' to ease restrictions of conformational transition resulting in a 'RBD-up' state, thereby conferring an adjustable infectivity. Furthermore, N354 glycosylation improved spike cleavage and cell-cell fusion, and in particular escaped one subset of ADCC antibodies. Together with reduced immunogenicity in hybrid immunity background, these indicate a single spike amino acid glycosylation event provides selective advantage in humans through multiple mechanisms.

A panel sequencing dataset of peripheral blood gene variations in pan-cancer.

Circulating cell-free DNA (cfDNA) in the peripheral blood is a promising biomarker for cancer diagnosis and prognosis. Somatic mutations identified in cancers have been used to detect therapeutic targets for clinical transformation and individualize drug selection, while germline variants can predict a patient's risk of developing cancer and drug sensitivity. However, no platform has been developed to analyze, calculate, integrate, and friendly visualize these pan-cancer cfDNA mutations deeply. In this work, we performed panel sequencing encompassing 1,115 cancer-related genes across 16,659 cancer patients, spanning 27 cancer types. We detected 496 germline variants in leukocytes and 11,232 somatic mutations in the cfDNA of all patients. CPGV (Cancer Peripheral blood Gene Variations), a database constructed from this dataset, is the first pan-cancer cfDNA database that encompasses somatic mutations, germline variants, and further comparative analyses of mutations across different cancer types. It bears great promise to serve as a valuable resource for cancer research.

[Development law of soil cracks in karst peak-cluster depressions under dry and wet alternations]. / 干湿交替条件下喀斯特峰丛洼地土壤裂隙发育规律.

In an experiment with alternating dry and wet conditions of soil in cultivated land, orchards and forest lands with limestone and dolomite in karst peak depression, combined with digital image processing technology, we investigated the development law of soil surface cracks under alternating dry and wet condition. The results showed that with the alternation of wet and dry, the average width of cracks decreased at a fast-slow-slower rate, with an order of limestone > dolomite under the same land use, and orchard > cultivated land > forest soil under the same soil-forming parent rock. In the first four dry and wet alternations, the degrees of soil fragmentation and connectivity were higher in dolomite development than in limestone, with significant differences in fracture development rose diagrams. In the subsequent cycles, soil fragmentation of most samples increased, the difference dominated by parent rock gradually decreased, the crack development rose diagram converged, and the connectivity showed the pattern of forest land > orchard > cultivated land. After the fourth cycle, the alternations of dry and wet seriously damaged soil structure. The physical and chemical properties of capillary porosity and non-capillary tube porosity were dominant in the development of cracks before that, but it was more dependent on the organic matter content and the sand composition after that.

MGA-seq: robust identification of extrachromosomal DNA and genetic variants using multiple genetic abnormality sequencing.

Genomic abnormalities are strongly associated with cancer and infertility. In this study, we develop a simple and efficient method - multiple genetic abnormality sequencing (MGA-Seq) - to simultaneously detect structural variation, copy number variation, single-nucleotide polymorphism, homogeneously staining regions, and extrachromosomal DNA (ecDNA) from a single tube. MGA-Seq directly sequences proximity-ligated genomic fragments, yielding a dataset with concurrent genome three-dimensional and whole-genome sequencing information, enabling approximate localization of genomic structural variations and facilitating breakpoint identification. Additionally, by utilizing MGA-Seq, we map focal amplification and oncogene coamplification, thus facilitating the exploration of ecDNA's transcriptional regulatory function.

The Study of the Transport Mechanism of Isorhynchophylline in Liver.

To investigate the transport mechanism of isorhynchophylline (IRN) by using the specific inhibitors of organic cation transporters (OCTs) and organic anion transporting polypeptides (OATPs) and attempt illustrate the metabolic mechanism of IRN in the liver. All animals were randomly divided into three groups: control group (only inject IRN), RIF group (inject IRN and rifampicin), and ADR group (inject IRN and adrenalone). The control group was injected with IRN via the caudal vein. The RIF group was injected with rifampicin (RIF) by gavage, and after 1 h, IRN was injected into the caudal vein. Similarly, the ADR group received adrenalone by the caudal vein, and after 0.5 h, IRN was injected into the caudal vein. Thereafter, blood samples were obtained by the heart punctures at 90 min, 180 min, and 300 min following drug administration. Rats were sacrificed at 300 min after drug administration; then, the liver tissue was harvested. The level of IRN was measured by using high-performance liquid chromatography (HPLC), and the Kp values were calculated. After RIF administration (OATPs inhibitors), the Kp value of IRN was slightly decreased when compared with that of the control group. Meanwhile, the Kp value of IRN was dramatically reduced compared to that of the control group following ADR administration (OCTs inhibitors). The results suggested that OCTs have mainly participated in the hepatic uptake process of IRN.

M6A-GSMS: Computational identification of N6-methyladenosine sites with GBDT and stacking learning in multiple species.

N6-methyladenosine (m6A) is one of the most abundant forms of RNA methylation modifications currently known. It involves a wide range of biological processes, including degradation, stability, alternative splicing, etc. Therefore, the development of convenient and efficient m6A prediction technologies are urgent. In this work, a novel predictor based on GBDT and stacking learning is developed to identify m6A sites, which is called M6A-GSMS. To achieve accurate prediction, we explore RNA sequence information from four aspects: correlation, structure, physicochemical properties and pseudo ribonucleic acid composition. After using the GBDT algorithm for feature selection, a stacking model is constructed by combining seven basic classifiers. Compared with other state-of-the-art methods, the results show that M6A-GSMS can obtain excellent performance for identifying the m6A sites. The prediction accuracy of A.thaliana, D.melanogaster, M.musculus, S.cerevisiae and Human reaches 88.4%, 60.8%, 80.5%, 92.4% and 61.8%, respectively. This method provides an effective prediction for the investigation of m6A sites. In addition, all the datasets and codes are currently available at https://github.com/Wang-Jinyue/M6A-GSMS.Communicated by Ramaswamy H. Sarma.

iPro-GAN: A novel model based on generative adversarial learning for identifying promoters and their strength.

BACKGROUND AND OBJECTIVE: Promoter is a component of the gene, which can specifically bind with RNA polymerase and determine where transcription starts, and also determine the transcription efficiency of the gene. Promoters can be divided into strong promoters and weak promoters because their structures and the interaction time interval are quite different. The functional variation of the promoter can lead to a variety of diseases. Therefore, identifying promoters and their strength is necessary and has important biological significance. A novel and promising model based on deep learning is proposed to achieve it. METHODS: In this work, we build a power model named iPro-GAN for identification of promoters and their strength. First, we collect benchmark datasets and independent datasets for training and testing. Then, Moran-based spatial auto-cross correlation method is used as feature extraction method. Finally, deep convolution generative adversarial network with 10-fold cross validation is applied for classifying. The first layer of the model is used to identify the promoter and the second layer is used to determine its type. RESULTS: On the benchmark data set, the accuracy of the first layer predictor is 93.15%, and the accuracy of the second layer predictor is 92.30%. On the independent data set, the accuracy of the first layer predictor is 86.77%, and the accuracy of the second layer predictor is 91.66%. In particular, breakthrough progress has been made in the identification of promoters' strength. CONCLUSIONS: These results are far higher than the existing best predictor, which indicate that our model is serviceable and practicable to identify promoters and their strength. Furthermore, the datasets and source codes are available from this link: https://github.com/Bovbene/iPro-GAN.