In large-scale high-throughput sequencing projects and biobank construction, sample tagging is essential to prevent sample mix-ups. Despite the availability of fingerprint panels for DNA data, little research has been conducted on sample tagging of whole genome bisulfite sequencing (WGBS) data. This study aims to construct a pipeline and identify applicable fingerprint panels to address this problem.Using autosome-wide A/T polymorphic single nucleotide variants (SNVs) obtained from whole genome sequencing (WGS) and WGBS of individuals from the Third China National Stroke Registry, we designed a fingerprint panel and constructed an optimized pipeline for tagging WGBS data. This pipeline used Bis-SNP to call genotypes from the WGBS data, and optimized genotype comparison by eliminating wildtype homozygous and missing genotypes, and retaining variants with identical genomic coordinates and reference/alternative alleles. WGS-based and WGBS-based genotypes called from identical or different samples were extensively compared using hap.py. In the first batch of 94 samples, the genotype consistency rates were between 71.01%-84.23% and 51.43%-60.50% for the matched and mismatched WGS and WGBS data using the autosome-wide A/T polymorphic SNV panel. This capability to tag WGBS data was validated among the second batch of 240 samples, with genotype consistency rates ranging from 70.61%-84.65% to 49.58%-61.42% for the matched and mismatched data, respectively. We also determined that the number of genetic variants required to correctly tag WGBS data was on the order of thousands through testing six fingerprint panels with different orders for the number of variants. Additionally, we affirmed this result with two self-designed panels of 1351 and 1278 SNVs, respectively. Furthermore, this study confirmed that using the number of genetic variants with identical coordinates and ref/alt alleles, or identical genotypes could not correctly tag WGBS data.This study proposed an optimized pipeline, applicable fingerprint panels, and a lower boundary for the number of fingerprint genetic variants needed for correct sample tagging of WGBS data, which are valuable for tagging WGBS data and integrating multi-omics data for biobanks.
To explore the prognostic value of early multiple detection indicators in combination with sequential organ failure assessment (SOFA) in sepsis patients.A retrospective analysis was conducted. Patients with sepsis admitted to the department of critical care medicine of Huanggang Central Hospital of Yangtze University from May 2020 to May 2022 were selected as the research subjects. Coagulation indicators, inflammatory factors, blood routine, liver and kidney function, and blood gas analysis were collected at admission. Organ dysfunction was assessed based on the SOFA score within 24 hours after admission. Patients were divided into a survival group and a death group according to the outcome of 28 days in ICU. Differences in the above indicators between the two groups were compared. Multifactorial Logistic regression analysis was used to analyze prognostic factors of 28-day mortality in sepsis patients. Receiver operator characteristic curve (ROC curve) was drawn to analyze the predictive performance of various indicators, the SOFA score, and the combine model for the 28-day outcome in patients with sepsis.A total of 101 patients with sepsis were enrolled, 56 patients survived and 45 patients died. Compared to the survival group, patients in the death group were older, the proportion of patients with septic shock was larger, the SOFA score, and the proportion of pulmonary infection were higher, the prothrombin time (PT) and activated partial thromboplastin time (APTT) were significantly prolonged, the prothrombin activity (PTA) was significantly shortened, and antithrombin (AT) was significantly decreased, the levels of hypersensitivity C-reactive protein (hs-CRP), blood urea nitrogen (BUN), total bilirubin (TBil), and lactic acid (Lac) were significantly increased, while the platelet count (PLT) was significantly decreased. Multifactorial Logistic regression analysis showed that pulmonary infection [odds ratio (OR) = 0.010, 95% confidence interval (95%CI) was 0.001-0.164, P = 0.001], AT (OR = 0.944, 95%CI was 0.910-0.978, P = 0.002), hs-CRP (OR = 1.008, 95%CI was 1.001-1.015, P = 0.017), Lac (OR = 1.619, 95%CI was 1.195-2.193, P = 0.002), and SOFA score (OR = 1.363, 95%CI was 1.076-1.727, P = 0.010) were independent prognostic factors for 28-day mortality in patients. A combined model was constructed using pulmonary infection, AT, hs-CRP, Lac, and SOFA score. ROC curve analysis showed that the area under the ROC curve (AUC) for the combine model in predicting sepsis prognosis was 0.936 (95%CI was 0.869-0.975, P < 0.001), which was higher in value compared to single indicators (AUC of AT, hs-CRP, Lac, and SOFA score were 0.775, 0.666, 0.802, 0.796, respectively, all P < 0.05).The predictive ability of the SOFA score for sepsis patient outcomes is limited. The combine model combining infection site, AT, hs-CRP, and Lac shows better predictive ability.
Backgrounds The role of O-GlcNAc transferase (OGT)-induced O-linked N-acetylglucosaminylation (O-GlcNAcylation) has been reported in multiple human diseases. However, its specific functions in osteoarthritis (OA) progression remain undetermined.
Abstract Various sensor‐based immunoassay methods have been extensively developed for the detection of cancer antigen 15‐3 (CA 15‐3), but most often exhibit low detection signals and low detection sensitivity, and are unsuitable for routine use. The aim of this work is to develop a simple and sensitive electrochemical immunoassay for CA 15‐3 in human serum by using nanogold and DNA‐modified immunosensors. Prussian blue (PB), as a good mediator, was initially electrodeposited on a gold electrode surface, then double‐layer nanogold particles and double‐strand DNA (dsDNA) with the sandwich‐type architecture were constructed on the PB‐modified surface in turn, and then anti‐CA 15‐3 antibodies were adsorbed onto the surface of nanogold particles. The double‐layer nanogold particles provided a good microenvironment for the immobilization of biomolecules. The presence of dsDNA enhanced the surface coverage of protein, and improved the sensitivity of the immunosensor. The performance and factors influencing the performance of the immunosensor were evaluated. Under optimal conditions, the proposed immunosensor exhibited a wide linear range from 1.0 to 240 ng/mL with a relatively low detection limit of 0.6 ng/mL ( S / N =3) towards CA 15‐3. The stability, reproducibility and precision of the as‐prepared immunosensor were acceptable. 57 serum specimens were assayed by the developed immunosensor and standard enzyme‐linked immunosorbent assay (ELISA), respectively, and the results obtained were almost consistent. More importantly, the proposed methodology could be further developed for the immobilization of other proteins and biocompounds.
Non-sentinel lymph node (NSLN) status prediction with molecular biomarkers may make some sentinel lymph node (SLN) positive breast cancer patients avoid the axillary lymph node dissection, but the available markers remain limited.SLN positive patients with and without NSLN invasion were selected, and genes differentially expressed or fused in SLN metastasis were screened by next-generation RNA sequencing.Six candidates (all ER/PR+, HER2-, Ki-67 <20%) with metastatic SLNs selected from 305 patients were equally categorized as NSLN negative and positive. We identified 103 specifically expressed genes in the NSLN negative group and 47 in the NSLN positive group. Among them, FABP1 (negative group) and CYP2A13 (positive group) were the only 2 protein-encoding genes with expression levels in the 8th to 10th deciles. Using a false discovery rate threshold of <0.05, 62 up-regulated genes and 98 down-regulated genes were discovered in the NSLN positive group. Furthermore, 10 gene fusions were identified in this group with the most frequently fused gene being IGLL5.The biomarkers screened in present study may broaden our understanding of the mechanisms of breast cancer metastasis to the lymph nodes and contribute to the axillary surgery selection for SLN positive patients.
Abstract With the rapid development of sequencing technologies towards higher throughput and lower cost, sequence data are generated at an unprecedentedly explosive rate. To provide an efficient and easy-to-use platform for managing huge sequence data, here we present Genome Sequence Archive (GSA; http://bigd.big.ac.cn/gsa or http://gsa.big.ac.cn), a data repository for archiving raw sequence data. In compliance with data standards and structures of the International Nucleotide Sequence Database Collaboration (INSDC), GSA adopts four data objects (BioProject, BioSample, Experiment, and Run) for data organization, accepts raw sequence reads produced by a variety of sequencing platforms, stores both sequence reads and metadata submitted from all over the world, and makes all these data publicly available to worldwide scientific communities. In the era of big data, GSA is not only an important complement to existing INSDC members by alleviating the increasing burdens of handling sequence data deluge, but also takes the significant responsibility for global big data archive and provides free unrestricted access to all publicly available data in support of research activities throughout the world.
Abstract In the case of mass disasters, missing persons and forensic caseworks, highly degraded biological samples are often encountered. It can be a challenge to analyze and interpret the DNA profiles from these samples. Here we provide a new strategy to solve the problem by taking advantage of the intrinsic structural properties of DNA. We have assessed the in vivo positions of more than 35 million putative nucleosome cores in human leukocytes using high-throughput whole genome sequencing, and identified 2,462 single nucleotide variations (SNVs), 128 insertion-deletion polymorphisms (indels). After comparing the sequence reads with 44 STR loci commonly used in forensics, five STRs (TH01, TPOX, D18S51, DYS391, and D10S1248)were matched. We compared these “nucleosome protected STRs” (NPSTRs) with five other non-NPSTRs using mini-STR primer design, real-time PCR, and capillary gel electrophoresis on artificially degraded DNA. Moreover, genotyping performance of the five NPSTRs and five non-NPSTRs was also tested with real casework samples. All results show that loci located in nucleosomes are more likely to be successfully genotyped in degraded samples. In conclusion, after further strict validation, these markers could be incorporated into future forensic and paleontology identification kits, resulting in higher discriminatory power for certain degraded sample types.
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