Identification of Sequence Variants in Genetic Disease-Causing Genes Using Targeted Next-Generation Sequencing

Identification of gene variants plays an important role in research on and diagnosis of genetic diseases. A combination of enrichment of targeted genes and next-generation sequencing (targeted DNA-HiSeq) results in both high efficiency and low cost for targeted sequencing of genes of interest.To identify mutations associated with genetic diseases, we designed an array-based gene chip to capture all of the exons of 193 genes involved in 103 genetic diseases. To evaluate this technology, we selected 7 samples from seven patients with six different genetic diseases resulting from six disease-causing genes and 100 samples from normal human adults as controls. The data obtained showed that on average, 99.14% of 3,382 exons with more than 30-fold coverage were successfully detected using Targeted DNA-HiSeq technology, and we found six known variants in four disease-causing genes and two novel mutations in two other disease-causing genes (the STS gene for XLI and the FBN1 gene for MFS) as well as one exon deletion mutation in the DMD gene. These results were confirmed in their entirety using either the Sanger sequencing method or real-time PCR.Targeted DNA-HiSeq combines next-generation sequencing with the capture of sequences from a relevant subset of high-interest genes. This method was tested by capturing sequences from a DNA library through hybridization to oligonucleotide probes specific for genetic disorder-related genes and was found to show high selectivity, improve the detection of mutations, enabling the discovery of novel variants, and provide additional indel data. Thus, targeted DNA-HiSeq can be used to analyze the gene variant profiles of monogenic diseases with high sensitivity, fidelity, throughput and speed

What Dense Graph Do You Need for Self-Attention?

Transformers have made progress in miscellaneous tasks, but suffer from quadratic computational and memory complexities. Recent works propose sparse Transformers with attention on sparse graphs to reduce complexity and remain strong performance. While effective, the crucial parts of how dense a graph needs to be to perform well are not fully explored. In this paper, we propose Normalized Information Payload (NIP), a graph scoring function measuring information transfer on graph, which provides an analysis tool for trade-offs between performance and complexity. Guided by this theoretical analysis, we present Hypercube Transformer, a sparse Transformer that models token interactions in a hypercube and shows comparable or even better results with vanilla Transformer while yielding $O(N\log N)$ complexity with sequence length $N$. Experiments on tasks requiring various sequence lengths lay validation for our graph function well.Comment: Accepted by ICML 2022. Code is available at https://github.com/yxzwang/Normalized-Information-Payloa

Burst Pressure Prediction of Subsea Supercritical CO2 Pipelines

To improve transportation efficiency, a supercritical CO2 pipeline is the best choice for large-scale and long-distance transportation inshore and offshore. However, corrosion of the pipe wall will occur as a result of the presence of free water and other impurities present during CO2 capture. Defects caused by corrosion can reduce pipe strength and result in pipe failure. In this paper, the burst pressure of subsea supercritical CO2 pipelines under high pressure is investigated. First, a mechanical model of corroded CO2 pipelines is established. Then, using the unified strength theory (UST), a new burst pressure equation for subsea supercritical CO2 pipelines is derived. Next, analysis of the material’s intermediate principal stress parameters is conducted. Lastly, the accuracy of the burst pressure equation of subsea supercritical CO2 pipelines is proven to meet the engineering requirement by experimental data. The results indicate that the parameter b of UST plays a significant role in determining burst pressure of pipelines. The study can provide a theoretical basis and reference for the design of subsea supercritical CO2 pipelines

Serotype distribution and antibiotic resistance of Streptococcus pneumoniae isolates from 17 Chinese cities from 2011 to 2016

Abstract Background Streptococcus pneumoniae, the leading pathogen of bacterial infections in infants and the elderly, is responsible for pneumococcal diseases with severe morbidity and mortality. Emergence of drug-resistant strains presented new challenges for treatment and prevention. Vaccination has proven to be an effective means of preventing pneumococcal infection worldwide. Detailed epidemiological information of antibiotic susceptibilities and serotype distribution will be of great help to the management of pneumococcal infections. Methods A total of 881 S. pneumoniae isolates were collected from patients at 23 teaching hospitals in 17 different cities from 2011 to 2016. The main specimen types included sputum, blood, broncho-alveolar lavage fluid, pharyngeal swabs, and cerebrospinal fluid. Minimum inhibitory concentrations (MICs) were determined using the agar dilution method. Capsular serotypes were identified using latex agglutination and quellung reaction test. Molecular epidemiology was investigated using multilocus sequence typing. Results S. pneumoniae isolates were highly resistant to macrolides, tetracycline, and trimethoprim/sulfamethoxazole. The rate of resistance to penicillin was 51.6% (oral breakpoint). However, levofloxacin and moxifloxacin maintained excellent antimicrobial activity and all of the isolated strains were susceptible to vancomycin. Twenty-two serotypes were identified among the 881 isolates. Prevalent serotypes were 19F (25.7%), 19A (14.0%), 15 (6.8%), 6B (3.6%), 6A (3.0%), and 17 (2.8%). The overall vaccine coverage rates for 7- and 13-valent pneumococcal conjugate vaccines were 37.5% and 58.3%, respectively. Vaccine coverage rates in young children and economically underdeveloped regions were higher than those in older adults and developed regions. Vaccine-covered serotypes demonstrated higher resistance compared with uncovered serotypes. Molecular epidemiological typing demonstrated that S. pneumoniae showed significant clonal dissemination and that ST271 (120, 28.3%), ST320 (73, 17.2%) and ST81 (27, 6.6%) were the major STs. Conclusions High resistance to clinical routine antibiotics was observed for all 881 S. pneumoniae strains. Drug resistance varied among different serotypes and age groups. Prevalent serotypes among the isolates were 19F, 19A, 15, 6B, 6A, and 17. Community-acquired strains should also be included in future studies to gain a better understanding of the prevalence and resistance of S. pneumoniae in China

Broadly neutralizing and protective nanobodies against SARS-CoV-2 Omicron subvariants BA.1, BA.2, and BA.4/5 and diverse sarbecoviruses

The authors identify nanobodies from immunized alpaca with broadly neutralizing activity against SARS-CoV-1, SARS-CoV-2 variants, and major sarbecoviruses. One representative nanobody binds to a highly conserved epitope on RBD and protects K18-hACE2 mice from Omicron and Delta infection

Targeted next-generation sequencing as a comprehensive test for patients with and female carriers of DMD/BMD:a multi-population diagnostic study

Duchenne and Becker muscular dystrophies (DMD/BMD) are the most commonly inherited neuromuscular disease. However, accurate and convenient molecular diagnosis cannot be achieved easily because of the enormous size of the dystrophin gene and complex causative mutation spectrum. Such traditional methods as multiplex ligation-dependent probe amplification plus Sanger sequencing require multiple steps to fulfill the diagnosis of DMD/BMD. Here, we introduce a new single-step method for the genetic analysis of DMD patients and female carriers in real clinical settings and demonstrate the validation of its accuracy. A total of 89 patients, 18 female carriers and 245 non-DMD patients were evaluated using our targeted NGS approaches. Compared with traditional methods, our new method yielded 99.99% specificity and 98.96% sensitivity for copy number variations detection and 100% accuracy for the identification of single-nucleotide variation mutations. Additionally, this method is able to detect partial deletions/duplications, thus offering precise personal DMD gene information for gene therapy. We detected novel partial deletions of exons in nine samples for which the breakpoints were located within exonic regions. The results proved that our new method is suitable for routine clinical practice, with shorter turnaround time, higher accuracy, and better insight into comprehensive genetic information (detailed breakpoints) for ensuing gene therapy