Copy number variation (CNV) is a key genetic characteristic for cancer diagnostics and can be used as a biomarker for the selection of therapeutic treatments. Using data sets established in our previous study, we benchmark the performance of cancer CNV calling by six most recent and commonly used software tools on their detection accuracy, sensitivity, and reproducibility. In comparison to other orthogonal methods, such as microarray and Bionano, we also explore the consistency of CNV calling across different technologies on a challenging genome.
While consistent results are observed for copy gain, loss, and loss of heterozygosity (LOH) calls across sequencing centers, CNV callers, and different technologies, variation of CNV calls are mostly affected by the determination of genome ploidy. Using consensus results from six CNV callers and confirmation from three orthogonal methods, we establish a high confident CNV call set for the reference cancer cell line (HCC1395).
NGS technologies and current bioinformatics tools can offer reliable results for detection of copy gain, loss, and LOH. However, when working with a hyper-diploid genome, some software tools can call excessive copy gain or loss due to inaccurate assessment of genome ploidy. With performance matrices on various experimental conditions, this study raises awareness within the cancer research community for the selection of sequencing platforms, sample preparation, sequencing coverage, and the choice of CNV detection tools.

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Plant synthetic biology research requires diverse bioparts that facilitate the redesign and construction of new-to-nature biological devices or systems in plants. Limited by few well-characterized bioparts for plant chassis, the development of plant synthetic biology lags behind that of its microbial counterpart. Here, we constructed a web-based Plant Synthetic BioDatabase (PSBD), which currently categorizes 1677 catalytic bioparts and 384 regulatory elements and provides information on 309 species and 850 chemicals. Online bioinformatics tools including local BLAST, chem similarity, phylogenetic analysis, and visual strength are provided to assist with the rational design of genetic circuits for manipulation of gene expression in planta. We demonstrated the utility of the PSBD by functionally characterizing taxadiene synthase 2 and its quantitative regulation in tobacco leaves. More powerful synthetic devices were then assembled to amplify the transcriptional signals, enabling enhanced expression of flavivirus non-structure 1 proteins in plants. The PSBD is expected to be an integrative and user-centered platform that provides a one-stop service for diverse applications in plant synthetic biology research.

We report three heterozygous PROS1 mutations that caused type I protein S deficiency in three unrelated Chinese families. We measured protein S activity and antigen levels for all participants, screened them for mutations in the PROS1 gene. And we employed the calibrated automated thrombin generation (CAT) method to investigate thrombin generation. Numerous bioinformatics tools were utilized to analyze the conservation, pathogenicity of mutation, and spatial structure of the protein S. Phenotyping analysis indicated that all three probands exhibited simultaneous reduced levels of PS:A, TPS:Ag, and FPS:Ag. Genetic testing revealed that proband A harbored a heterozygous c.458_458delA (p.Lys153Serfs*6) mutation in exon 5, proband B carried a heterozygous c.1687C>T (p.Gln563stop) mutation in exon 14, and proband C exhibited a heterozygous c.200A>C (p.Glu67Ala) mutation in exon 2. Bioinformatic analysis predicted that the p.Lys153Serfs*6 frameshift mutation and the p.Gln563stop nonsense mutation in the protein S were classified as \"disease-causing.\" The identification of the novel mutation p.Lys153Serfs*6 in PROS1 enriches the Human Genome Database. Our research suggests that these three mutations (p.Lys153Serfs*6, p.Gln563stop, and p.Glu67Ala) are possibly responsible for the decreased level of protein S in the three families. Furthermore, the evidence also supports the notion that individuals who are asymptomatic but have a family history of PSD can benefit from genetic analysis of the PROS1 gene.

The advancement of mass spectrometry technologies has revolutionised plant metabolomics research by enabling the acquisition of raw metabolomics data. However, the identification, analysis, and visualisation of these data require specialised tools. Existing solutions lack a dedicated plant-specific metabolite database and pose usability challenges. To address these limitations, we developed PlantMetSuite, a web-based tool for comprehensive metabolomics analysis and visualisation. PlantMetSuite encompasses interactive bioinformatics tools and databases specifically tailored to plant metabolomics data, facilitating upstream-to-downstream analysis in metabolomics and supporting integrative multi-omics investigations. PlantMetSuite can be accessed directly through a user\'s browser without the need for installation or programming skills. The tool is freely available and will undergo regular updates and expansions to incorporate additional libraries and newly published metabolomics analysis methods. The tool\'s significance lies in empowering researchers with an accessible and customisable platform for unlocking plant metabolomics insights.

Precisely calling chromatin loops has profound implications for further analysis of gene regulation and disease mechanisms. Technological advances in chromatin conformation capture (3C) assays make it possible to identify chromatin loops in the genome. However, a variety of experimental protocols have resulted in different levels of biases, which require distinct methods to call true loops from the background. Although many bioinformatics tools have been developed to address this problem, there is still a lack of special introduction to loop-calling algorithms. This review provides an overview of the loop-calling tools for various 3C-based techniques. We first discuss the background biases produced by different experimental techniques and the denoising algorithms. Then, the completeness and priority of each tool are categorized and summarized according to the data source of application. The summary of these works can help researchers select the most appropriate method to call loops and further perform downstream analysis. In addition, this survey is also useful for bioinformatics scientists aiming to develop new loop-calling algorithms.

Tuberculosis is a chronic consumptive infectious disease, which can cause great damage to human and animal health all over the world. The emergence of multi-drug resistant strains, the unstable protective effect of Bacillus Calmette-Guérin (BCG) vaccine on adults, and the mixed infection with HIV all warn people to exploit new approaches for conquering tuberculosis. At present, there has been significant progress in developing tuberculosis vaccines, such as improved BCG vaccine, subunit vaccine, DNA vaccine, live attenuated vaccine and inactivated vaccine. Among these candidate vaccines, there are some promising vaccines to improve or replace BCG vaccine effect. Meanwhile, the application of adjuvants, prime-boost strategy, immunoinformatic tools and targeting components have been studied concentratedly, and verified as valid means of raising the efficiency of tuberculosis vaccines as well. In this paper, the latest advance in tuberculosis vaccines in recent years is reviewed to provide reliable information for future tuberculosis prevention and treatment.

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Interleukin-6 (IL-6) has been reported to induce osteogenic differentiation of mesenchymal stem cells for increasing bone regeneration, while the role of IL-6 in osteogenic differentiation during ossification of the posterior longitudinal ligament (OPLL) remains to be determined. The current study aims to explore the downstream mechanism of IL-6 in cyclic tensile strain (CTS)-stimulated OPLL, which involves bioinformatically identified microRNA-135b (miR-135b). Initially, we clinically collected posterior longitudinal ligament (PLL) and ossified PLL tissues, from which ossified PLL cells were isolated, respectively. The obtained data revealed a greater osteogenic property of ossified PLL than non-ossified PLL cells. The effect of regulatory axis comprising IL-6, Stat3, miR-135b, and BMPER on osteogenic differentiation of CTS-stimulated ossified PLL cells was examined with gain- and loss-of-function experiments. BMPER was confirmed as a target gene to miR-135b. Knockdown of BMPER or overexpression of miR-135b inhibited the osteogenic differentiation of CTS-induced ossification in PLL cells. Besides, IL-6 promoted the post-transcriptional process to mature miR-135b via Stat3 phosphorylation. In conclusion, IL-6 inhibited CTS-induced osteogenic differentiation by inducing miR-135b-mediated inhibition of BMPER through Stat3 activation.

Background: Nardilysin, (N-arginine dibasic convertase, NRDC) has been reported to play an important role in cancer progression, and is associated with tumor proliferation signals and inflammatory signals, such as tumor necrosis factor-a (TNF-a) and heparin-binding epidermal growth factor-like growth factor (HB-EGF), through the activation of disintegrin and metalloproteinase (ADAM) proteases. NRDC has recently been revealed to be involved in the tumorigenesis of various types of cancer, including intrahepatic cholangiocarcinoma, malignant cerebral infarction, esophageal squamous cell carcinoma, and gastric cancer. However, the expression profiles and biological relevance of NRDC in pancreatic ductal adenocarcinoma have rarely been reported. Methods: We analyzed the NRDC expression profile in pancreatic ductal adenocarcinoma by enzyme-linked immunosorbent assay (ELISA) and identified NRDC as a circulating biomarker in the serum of 112 pancreatic ductal adenocarcinoma patients. The diagnostic value of NRDC was analyzed by the area under the curve (AUC) and the receiver operating characteristic (ROC) test. Results: Our results demonstrated that the clinical prognosis significance of NRDC with the clinical characteristics in pancreatic ductal adenocarcinoma (PDAC). NRDC was notably decreased in PDAC patient serum compared with the control group (p < 0.001). Furthermore, the present study found that the NRDC expression level was correlated with T grade (p < 0.001), metastasis(p < 0.001), differentiation(p < 0.001), and TNM stage (p = 0.011). Further bioinformatics analysis revealed that NRDC correlated with proliferation and migration pathways; in particular, it mediated cell-matrix adhesion-dependent activation in pancreatic ductal adenocarcinoma. Conclusions: Serum NRDC may play a useful diagnostic biomarker to evaluate the aggressive clinical features in PAAD patients.