Genomics, proteomics & bioinformatics最新文献

{"title":"Correction to: ProtPipe: A Multifunctional Data Analysis Pipeline for Proteomics and Peptidomics.","authors":"","doi":"10.1093/gpbjnl/qzaf051","DOIUrl":"10.1093/gpbjnl/qzaf051","url":null,"abstract":"","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":"23 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12206521/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144531958","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Implication of The Vaginal Microbiome in Female Infertility and Assisted Conception Outcomes.","authors":"Xiuju Chen, Yanyu Sui, Jiayi Gu, Liang Wang, Ningxia Sun","doi":"10.1093/gpbjnl/qzaf042","DOIUrl":"https://doi.org/10.1093/gpbjnl/qzaf042","url":null,"abstract":"<p><p>The rise in infertility rates has prompted research into the impact of vaginal microbiota on female fertility and assisted reproduction technology (ART) success. Our study compares the vaginal microbiome of fertile and infertile women and explores its influence on ART outcomes. We analyzed vaginal secretions from 194 infertile women and 100 healthy controls at Shanghai Changzheng Hospital using polymerase chain reaction (PCR) to amplify the 16S rRNA V3-V4 region. A machine learning model predicted infertility based on genus abundances, and the PICRUSt algorithm predicted metabolic pathways related to infertility and ART outcome. The results showed women with infertility exhibited a significantly different vaginal microbial composition compared to healthy women, with the infertility group showing higher microbial diversity. Burkholderia, Pseudomonas, and Prevotella levels were significantly elevated in the vaginal microbiota of the infertility group, while Bifidobacterium and Lactobacillus abundances were reduced. Recurrent implantation failure (RIF) within the infertile population showed even higher diversity of vaginal microbiota, with specific genera such as Mobiluncus, Peptoniphilus, Prevotella, and Varibaculum being more abundant. Eleven metabolic pathways were associated with RIF and infertility, with Prevotella demonstrating stronger correlations. The present study provides insights into the differences in vaginal microbiome between healthy and infertile women, offering a new understanding of how vaginal microbiota may impact infertility and ART outcomes. Our findings underscore the significance of specific microbial taxa in women with RIF, suggesting avenues for targeted interventions to enhance embryo transplantation success rates.</p>","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144047396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrative Genome-wide Association Meta-analysis of Aortic Aneurysm and Dissection Identifies Five Novel Genes.","authors":"Yifan Du, Yunlong Guan, Zhonghe Shao, Minghui Jiang, Minghan Qu, Yifan Kong, Hongji Wu, Da Luo, Shu Peng, Si Li, Xi Cao, Jing Chen, Ping Ye, Jiahong Xia, Xingjie Hao","doi":"10.1093/gpbjnl/qzaf039","DOIUrl":"https://doi.org/10.1093/gpbjnl/qzaf039","url":null,"abstract":"<p><p>Aortic aneurysm and dissection (AAD) is a multifaceted condition characterized by significant genetic predisposition and a considerable contribution to cardiovascular-related mortality. Previous studies have suggested that AAD subtypes share similar genetic mechanisms, however, these studies investigated the subtypes separately. Here, we performed a large genome-wide association study (GWAS) meta-analysis for AAD by combining its subtypes, including 11,148 cases and 708,468 controls of European ancestry. We identified 24 susceptibility loci, including four novel loci at 1p21.2 (PALMD), 2p22.2 (CRIM1), 6q22.1 (FRK), and 12q14.3 (HMGA2), which were partially validated in both internal and external populations. Cell type-specific analysis highlighted the artery as the most relevant tissue where the susceptibility variants may exert their effects in a tissue-specific manner. By using four approaches, we prioritized 53 genes, reinforcing the importance of elastic fiber formation and transforming growth factor-beta (TGF-β) signaling in the formation of AAD, and suggested potential target drugs for the treatment. Additionally, various cardiovascular diseases were genetically correlated with AAD, and several cardiovascular risk factors [e.g., body mass index (BMI), lipid levels, and pulse pressure] showed causal associations with AAD, underscoring their shared genetic structures and mechanisms underlying the comorbidity. Moreover, five prioritized genes (PALMD, CRIM1, FRK, HMGA2, and NT5DC1) at the novel loci were supported as regulators of smooth muscle and endothelial cell functions through ex vivo and in vitro experiments. Together, these findings enhance our understanding of the genetic architecture of AAD and provide novel insights into future biological mechanism studies and therapeutic strategies.</p>","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144039586","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The High Expression of PD-1 Defines A Subpopulation of Tfh Cells Responding to COVID-19 Vaccine in Humans.","authors":"Jingxin Guo, Zhangfan Fu, Yi Zhang, Mengyuan Xu, Jinhang He, Haocheng Zhang, Qiran Zhang, Jieyu Song, Ke Lin, Mingxiang Fan, Zhangyufan He, Guanmin Yuan, Ning Jiang, Huang Huang, Chao Qiu, Jingwen Ai, Wenhong Zhang","doi":"10.1093/gpbjnl/qzaf019","DOIUrl":"https://doi.org/10.1093/gpbjnl/qzaf019","url":null,"abstract":"<p><p>Inactivated coronavirus disease 2019 (COVID-19) vaccines and receptor binding domain subunit (RBD-subunit) booster vaccination can induce effective humoral immune response. CD4+ T helper cells are essential in helping B cells and antibody response. However, the response of CD4+ T cells to booster vaccination, especially the virus-induced T follicular helper (Tfh) cells, needs to be better characterized. In this study, it was investigated using tools of single-cell sequencing and flow cytometry. Additionally, a customized analysis algorithm was applied to identify virus-induced T cell receptor (VI-TCR) which is useful to explore the activation and persistence of virus-induced CD4+ T cell response. We identified a subset of classic Tfh (cTfh) cells with high expression of PD-1 and IFN-γ. They were notably activated following booster vaccination, and their proportion was correlated with the antibody titer level. We used trajectory analysis to analyze the dynamic changes of activated and found that a subset of virus-induced cTfh cells might maintain immune responses beyond 90 days post-vaccination. In summary, we found a group of PD-1high cTfh cells in COVID-19 vaccination, which can enhance the humoral response and show the persistence of immune response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We also provided a method for single-cell immune data analysis to understand the virus-induced responses. Understanding how cTfh cells help antibody production will provide essential insights into the rational design of new vaccine strategies to optimize long-term immunity.</p>","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143627250","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"High-quality Population-specific Haplotype-resolved Reference Panel in the Genomic and Pangenomic Eras.","authors":"Qingxin Yang, Yuntao Sun, Shuhan Duan, Shengjie Nie, Chao Liu, Hong Deng, Mengge Wang, Guanglin He","doi":"10.1093/gpbjnl/qzaf022","DOIUrl":"https://doi.org/10.1093/gpbjnl/qzaf022","url":null,"abstract":"<p><p>Large-scale international and regional human genomic and pangenomic resources derived from population-scale biobanks and ancient DNA sequences have provided significant insights into human evolution and the genetic determinants of complex diseases and traits. Despite these advances, challenges persist in optimizing the integration of phasing tools, merging haplotype reference panels (HRPs), developing imputation algorithms, and fully exploiting the diverse applications of post-imputation data. This review comprehensively summarizes the advancements, applications, limitations, and future directions of HRPs in human genomics research. Recent progress in the reconstruction of HRPs, based on over 830,000 human whole-genome sequences, has been synthesized, highlighting the broad spectrum of human genetic diversity captured. Additionally, we recapitulate advancements in fifty-six HRPs for global and regional populations. The evaluation of imputation accuracy indicated that Beagle and GLIMPSE are the most effective tools for phasing and imputing data from genotyping arrays and low-coverage sequencing, respectively. A critical strategy for selecting an appropriate HRP involves matching the population background of target groups with HRP reference populations and considering multi-ancestry or homogeneous genetic structures. The necessity of a single, integrative, high-quality HRP that captures haplotype structures and genetic diversity across various genetic variation types from globally representative populations is emphasized to support both modern and ancient genomic research and advance human precision medicine.</p>","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143588971","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"LigExtract: Large-scale Automated Identification of Ligands from Protein Structures in the Protein Data Bank.","authors":"Natália Aniceto, Nuno Martinho, Ismael Rufino, Rita C Guedes","doi":"10.1093/gpbjnl/qzaf018","DOIUrl":"https://doi.org/10.1093/gpbjnl/qzaf018","url":null,"abstract":"<p><p>The Protein Data Bank is an ever-growing database of 3D macromolecular structures that has become a crucial resource for the drug discovery process. Exploring complexed proteins and accessing the ligands in these proteins is paramount to help researchers understand biological processes and design new compounds of pharmaceutical interest. However, currently available tools to perform large-scale ligand identification do not address many of the more complex ways in which ligands are stored and represented in PDB structures. Therefore, a new tool called LigExtract was specifically developed for the large-scale processing of PDB structures and the identification of their ligands. This is a fully open-source tool available to the scientific community, designed to provide end-to-end processing whereby the user simply provides a list of UniProt IDs and LigExtract returns a list of ligands, their individual PDB files, a PDB file of the protein chains engaged with the ligand and a series of log files that inform the user of the decisions made during the ligand extraction process as well as potential flagging of additional scenarios that might have to be considered during any follow-up use of the processed files (e.g., ligands covalently bound to the protein). LigExtract is available, open-source, on GitHub (https://github.com/comp-medchem/LigExtract).</p>","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143560407","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Single-cell Sequencing Traces Mitochondrial Transfers.","authors":"Mengying Wu, Weilin Pu, Zhenglong Gu","doi":"10.1093/gpbjnl/qzae092","DOIUrl":"10.1093/gpbjnl/qzae092","url":null,"abstract":"","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11806949/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142901429","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Novel IgG-IgM Autoantibody Panel Enhances Detection of Early-stage Lung Adenocarcinoma from Benign Nodules.","authors":"Rongrong Luo, Xiying Li, Ruyun Gao, Mengwei Yang, Juan Cai, Liyuan Dai, Nin Lou, Guangyu Fan, Haohua Zhu, Shasha Wang, Zhishang Zhang, Le Tang, Jiarui Yao, Di Wu, Yuankai Shi, Xiaohong Han","doi":"10.1093/gpbjnl/qzae085","DOIUrl":"10.1093/gpbjnl/qzae085","url":null,"abstract":"<p><p>Autoantibodies hold promise for diagnosing lung cancer. However, their effectiveness in early-stage detection needs improvement. In this study, we investigated novel IgG and IgM autoantibodies for detecting early-stage lung adenocarcinoma (Early-LUAD) by employing a multi-step approach, including Human Proteome Microarray (HuProtTM) discovery, focused microarray verification, and ELISA validation, on 1246 individuals consisting of 634 patients with Early-LUAD (stage 0-I), 280 patients with benign lung disease (BLD), and 332 normal healthy controls (NHCs). HuProtTM selected 417 IgG/IgM candidates, and focused microarray further verified 55 significantly elevated IgG/IgM autoantibodies targeting 32 tumor-associated antigens in Early-LUAD compared to BLD/NHC/BLD+NHC. A novel panel of 10 autoantibodies (ELAVL4-IgM, GDA-IgM, GIMAP4-IgM, GIMAP4-IgG, MGMT-IgM, UCHL1-IgM, DCTPP1-IgM, KCMF1-IgM, UCHL1-IgG, and WWP2-IgM) demonstrated a sensitivity of 70.5% and a specificity of 77.0% or 80.0% for distinguishing Early-LUAD from BLD or NHC in ELISA validation. Positive predictive values for distinguishing Early-LUAD from BLD with nodules ≤ 8 mm, 9-20 mm, and > 20 mm significantly increased from 47.27%, 52.00%, and 62.90% [low-dose computed tomography (LDCT) alone] to 79.17%, 71.13%, and 87.88% (10-autoantibody panel combined with LDCT), respectively. The combined risk score (CRS), based on the 10-autoantibody panel, sex, and imaging maximum diameter, effectively stratified the risk for Early-LUAD. Individuals with 10 ≤ CRS ≤ 25 and CRS > 25 indicated a higher risk of Early-LUAD compared to the reference (CRS < 10), with adjusted odds ratios of 5.28 [95% confidence interval (CI): 3.18-8.76] and 9.05 (95% CI: 5.40-15.15), respectively. This novel panel of IgG and IgM autoantibodies offers a complementary approach to LDCT in distinguishing Early-LUAD from benign nodules.</p>","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12032526/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142815375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"SoyOD: An Integrated Soybean Multi-omics Database for Mining Genes and Biological Research.","authors":"Jie Li, Qingyang Ni, Guangqi He, Jiale Huang, Haoyu Chao, Sida Li, Ming Chen, Guoyu Hu, James Whelan, Huixia Shou","doi":"10.1093/gpbjnl/qzae080","DOIUrl":"10.1093/gpbjnl/qzae080","url":null,"abstract":"<p><p>Soybean is a globally important crop for food, feed, oil, and nitrogen fixation. A variety of multi-omics studies have been carried out, generating datasets ranging from genotype to phenotype. In order to efficiently utilize these data for basic and applied research, a soybean multi-omics database with extensive data coverage and comprehensive data analysis tools was established. The Soybean Omics Database (SoyOD) integrates important new datasets with existing public datasets to form the most comprehensive collection of soybean multi-omics information. Compared to existing soybean databases, SoyOD incorporates an extensive collection of novel data derived from the deep-sequencing of 984 germplasms, 162 novel transcriptomic datasets from seeds at different developmental stages, 53 phenotypic datasets, and more than 2500 phenotypic images. In addition, SoyOD integrates existing data resources, including 59 assembled genomes, genetic variation data from 3904 soybean accessions, 225 sets of phenotypic data, and 1097 transcriptomic sequences covering 507 different tissues and treatment conditions. Moreover, SoyOD can be used to mine candidate genes for important agronomic traits, as shown in a case study on plant height. Additionally, powerful analytical and easy-to-use toolkits enable users to easily access the available multi-omics datasets, and to rapidly search genotypic and phenotypic data in a particular germplasm. The novelty, comprehensiveness, and user-friendly features of SoyOD make it a valuable resource for soybean molecular breeding and biological research. SoyOD is publicly accessible at https://bis.zju.edu.cn/soyod.</p>","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11757165/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142635076","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep Amplicon Sequencing Reveals Culture-dependent Clonal Selection of Mycobacterium tuberculosis in Clinical Samples.","authors":"Jiuxin Qu, Wanfei Liu, Shuyan Chen, Chi Wu, Wenjie Lai, Rui Qin, Feidi Ye, Yuanchun Li, Liang Fu, Guofang Deng, Lei Liu, Qiang Lin, Peng Cui","doi":"10.1093/gpbjnl/qzae046","DOIUrl":"10.1093/gpbjnl/qzae046","url":null,"abstract":"<p><p>The commonly-used drug susceptibility testing (DST) relies on bacterial culture and faces shortcomings such as long turnaround time and clonal/subclonal selection biases. Here, we developed a targeted deep amplicon sequencing (DAS) method directly applied to clinical specimens. In this DAS panel, we examined 941 drug-resistant mutations (DRMs) associated with 20 anti-tuberculosis drugs with only 4 pg of initial DNA input, and reduced the clinical testing time from 20 days to 2 days. A prospective study was conducted using 115 clinical specimens, predominantly positive for the Xpert®  Mycobacterium tuberculosis/rifampicin (Xpert MTB/RIF) assay, to evaluate DRM detection. DAS was performed on culture-free specimens, while culture-dependent isolates were used for phenotypic DST, DAS, and whole-genome sequencing (WGS). For in silico molecular DST, our result based on DAS panel revealed the similar accuracy to three published reports based on WGS. For 82 isolates, application of DAS using the resistance-determining mutation method showed better accuracy (93.03% vs. 92.16%), sensitivity (96.10% vs. 95.02%), and specificity (91.33% vs. 90.62%) than WGS using the Mykrobe software. Compared to culture-dependent WGS, culture-free DAS provides a full picture of sequence variation at the population level, exhibiting in detail the gain-and-loss variants caused by bacterial culture. Our study performs a systematic verification of the advantages of DAS in clinical applications and comprehensively illustrates the discrepancies in Mycobacterium tuberculosis before and after culture.</p>","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11978391/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141319301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}