Genomics, proteomics & bioinformatics最新文献

{"title":"SAA1 Promotes Pro-inflammatory Macrophage-mediated Bone Invasion in Silent Corticotroph Adenomas.","authors":"Jingyuan Jia, Chenggang Jiang, Jindou Xie, Zhaoyi Yi, Han Di, Xuejing Li, Lei Zhou, Lu Bai, Yuwei Liu, Renlong Zhang, Lei Gong, Hongyun Wang, Zhaoqi Liu, Weiyan Xie, Chuzhong Li, Xudong Xing, Yazhuo Zhang","doi":"10.1093/gpbjnl/qzag064","DOIUrl":"https://doi.org/10.1093/gpbjnl/qzag064","url":null,"abstract":"<p><p>Silent corticotroph adenomas (SCAs) represent a high-risk subtype of pituitary neuroendocrine tumors, characterized by significant clinical heterogeneity and unclear pathogenesis. The multimicrocystic sign is a typical radiological feature of SCAs; however, its biological significance remains unclear. Here, we show that the characteristics of cystic changes reflect tumor evolutionary stages and are correlated with invasiveness and proliferative activity. We performed multi-omics analysis to identify key molecular drivers and revealed that serum amyloid A1 (SAA1) is highly expressed in microcystic tumors corresponding to the bone invasion stage. Our results demonstrate that SAA1 activates the TLR4/NF-κB pathway in macrophages, promoting pro-inflammatory macrophage polarization, TNF-α and CSF-1 secretion, and osteoclast differentiation. Spatial transcriptomics confirmed a significant correlation between the proportion of SAA1+ tumor cells and that of TNF-α+ macrophages. Serum amyloid A (SAA) levels in serum exhibited strong diagnostic value for SCAs. These findings highlight the potential clinical and biological significance of cyst size in SCAs and uncover a novel mechanism by which SAA1 drives tumor bone invasiveness through macrophage-mediated osteoclast differentiation. Our findings highlight that serum SAA levels may serve as a promising biomarker for the preoperative identification of SCAs, advancing our understanding of SCA heterogeneity.</p>","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":7.9,"publicationDate":"2026-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148458230","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 Mutation Rates in Non-human Primates Edited by Cytosine Base Editors.","authors":"Wenwen Shi, Shao-Jie Zhang, Wushuang Rui, Tong Zhou, Ya-Ping Zhang, Guo-Dong Wang, Yong Q Zhang","doi":"10.1093/gpbjnl/qzag063","DOIUrl":"https://doi.org/10.1093/gpbjnl/qzag063","url":null,"abstract":"<p><p>Gene-edited animals are being produced and used in ever-increasing numbers. However, their genome-wide mutation rates remain largely unknown. To characterize the mutation rates in animals edited by different gene editors, we analysed the publicly available genome sequencing datasets of parent-offspring trios. Unexpectedly, we found that the mutation rate in non-human primates edited by cytosine base editors (CBEs) was extremely high, approximately 158-fold higher than the unedited controls, while the mutation rate in CBE-edited mice was about 4-fold higher than unedited mice. Our results highlight the necessity to evaluate whole-genome de novo mutations using a streamlined analysis pipeline when CBEs are used to manipulate target genes in animals, especially when they are used for translational medicine.</p>","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":7.9,"publicationDate":"2026-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148431768","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":"NTM-DB: A Comprehensive Non-tuberculosis Mycobacteria Genomic Database.","authors":"Tianyi Lu, Cuidan Li, Haobin Wei, Yadong Zhang, Zhuojing Fan, Xiaoyuan Jiang, Jie Wang, Peihan Wang, Kang Shang, Yuting Huang, Hongwei Yang, Bahetibieke Tuohetaerbaike, Ying Li, Haitao Niu, Wenbao Zhang, Hao Wen, Yongjie Sheng, Jingfa Xiao, Fei Chen","doi":"10.1093/gpbjnl/qzag062","DOIUrl":"https://doi.org/10.1093/gpbjnl/qzag062","url":null,"abstract":"<p><p>Non-tuberculous mycobacteria (NTM) are a major group of environmental bacteria, approximately one-third of which cause serious human infections, particularly respiratory diseases. The global rise in the prevalence and severity of NTM infections has posed a major public health challenge. While high-throughput sequencing has generated vast genomic data on NTM, there remains a lack of comprehensive resources for cross-species genomic analysis. To address these limitations, we developed a specialized database, the Non-tuberculosis Mycobacteria Genomic Database (NTM-DB), tailored for NTM researchers and clinicians. NTM-DB offers the most comprehensive collection of NTM genomic and bioinformatic resources, including 16,469 genome assemblies (13,134 newly assembled genomes), 189 type/standard strain genomes representing 177 species and 12 subspecies, 705 multi-locus sequence typing (MLST) types, 33,240 resistance genes, and 74,315 virulence genes. A user-friendly interactive website was constructed to enable efficient browsing, MLST profiling, searching, online analysis, and downloading of the aforementioned data. Notably, with online analysis tools, users can perform customized genotyping, cross-species phylogeny, pan-genome, and virulence and drug resistance gene annotation analyses using our data and/or their uploaded data. Overall, with its comprehensive data, intuitive interface, and powerful analysis tools, NTM-DB serves as an important resource and reference for NTM researchers and clinicians, thereby improving the diagnosis and treatment of various NTM-related diseases and supporting both scientific discovery and clinical practice. NTM-DB is publicly accessible at https://ngdc.cncb.ac.cn/ntmdb.</p>","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":7.9,"publicationDate":"2026-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148427790","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":"TNEAtlas: A Pan-cancer Database to Identify and Characterize Transcribed Non-coding Elements.","authors":"Wenyong Zhu, Rongxin Zhang, Xiao Sun","doi":"10.1093/gpbjnl/qzag061","DOIUrl":"https://doi.org/10.1093/gpbjnl/qzag061","url":null,"abstract":"<p><p>Advances in precision oncology have underscored the need to move beyond regulatory frameworks centered on protein-coding regions and better understand regulatory mechanisms within the non-coding genome. To systematically characterize transcribed non-coding elements (TNEs) in cancer, we developed an automated computational framework that integrates 130 RNA-seq datasets from 26 cancer types and 16 human tissues and identifies more than 2 million intergenic TNEs. In parallel, we established the first pan-cancer TNE database, TNEAtlas, which annotates TNEs with epigenetic signatures and functional features. Our analyses revealed that TNEs act as molecular switches that drive tumor evolution through conserved regulatory functions, tissue-specific transcription factor recruitment, and epigenetic modification crosstalk. We also demonstrated that these TNEs exhibit structural motif preferences, especially G-quadruplexes, and tumor heterogeneity patterns consistent with cancer subtype classifications. Our database implemented an interactive platform comprising dynamic visualization tools, integrated analysis modules, and structured data resources to enable the exploration of TNE regulatory networks across multi-omics data. Our database provides a systematic framework for decoding non-coding genome regulation in carcinogenesis by combining transcriptional activity, chromatin architecture, tumor microenvironment interactions, and comprehensive pharmacological data. Overall, our database not only advances precision medicine by facilitating the identification of functional TNEs but also offers comprehensive analysis frameworks of the non-coding cancer genome, providing the scientific community with an open-access platform that bridges fragmented TNE studies with systematic exploration of genomic machinery and remains scalable for future discoveries in the non-coding cancer genome. TNEAtlas is publicly accessible at https://www.seubioinfo.cn/tneatlas.</p>","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":7.9,"publicationDate":"2026-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148414349","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":"Long-read Sequencing: from Complete Molecules to Context-resolved Biology.","authors":"Wanlu Liu, Hui Shen, Yi Xing","doi":"10.1093/gpbjnl/qzag058","DOIUrl":"https://doi.org/10.1093/gpbjnl/qzag058","url":null,"abstract":"","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":7.9,"publicationDate":"2026-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148400438","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 RNA Sequencing Reveals A Tumor-Promoting Role of EGR1+CD4+ T Cells in Papillary Thyroid Cancer.","authors":"Zhengshi Wang, Yun Zhang, Yong Xu, Zhaohui Liu, Shengyun Wang, Zhiqiang Yin, Youlutuziayi Rixiati","doi":"10.1093/gpbjnl/qzag060","DOIUrl":"https://doi.org/10.1093/gpbjnl/qzag060","url":null,"abstract":"<p><p>Papillary thyroid cancer (PTC) is the most common thyroid malignancy. Based on single-cell RNA sequencing, a previously unrecognized CD4+ T cell subset was identified, termed EGR1+CD4+ T cells. This subset produced high levels of IL-10 and IFN-γ in response to phorbol 12-myristate 13-acetate (PMA) and ionomycin, and showed distinct molecular pathway activity compared to CD4+ Tregs. CD4+ T cell-specific overexpression of EGR1 in vitro enhanced tumor cell proliferation, invasion, and migration when co-cultured with PTC cell lines. The expression profiling analysis of immune checkpoint molecules indicated that CD96 was commonly up-regulated in EGR1+CD4+ T cells, CD4+ Tregs, and other T cell subsets, especially in tumor tissues. Single CD96 blockade significantly increased the levels of IFN-γ, IL-17a, and IL-10 in EGR1+CD4+ T cells and inhibited the proliferation of PTC tumor cells. Co-blockade of CD96/TIGIT significantly enhanced the production of IFN-γ, TNF-α, and IL-17a in both EGR1+CD4+ T cells and CD3+CD4+ T cells, which also suppressed cell proliferation, invasion, and migration when co-cultured with PTC tumor cells. These findings indicated that EGR1+CD4+ T cells were a novel CD4+ T cell subset with specific functions. Single CD96 blockade or co-blockade of CD96/TIGIT enhanced antitumor immunity of EGR1+CD4+ T cells, which might be promising therapeutic strategies in PTC treatment.</p>","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":7.9,"publicationDate":"2026-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148400425","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":"A Cattle BodyMap of Transcriptome across 52 Tissues and 3 Developmental Stages Reveals New Genetic Insights into Beef Production Traits.","authors":"Wentao Cai, Yapeng Zhang, Lei Xu, Yahui Wang, Xin Hu, Qian Li, Linxi Zhu, Zezhao Wang, Huijiang Gao, Lingyang Xu, Junya Li, Lupei Zhang","doi":"10.1093/gpbjnl/qzag057","DOIUrl":"https://doi.org/10.1093/gpbjnl/qzag057","url":null,"abstract":"<p><p>Cattle are important livestock that provide essential meat and milk resources. However, a comprehensive analysis of gene expression, alternative splicing (AS), and RNA editing across various organs and developmental stages in cattle has not been reported. This study aims to create a comprehensive transcriptomic BodyMap across various tissues and developmental stages, integrating this information into genomic predictions of beef production traits. We created a comprehensive transcriptomic BodyMap using 400 samples collected from 52 organs of newborn, young, and adult cattle, and estimated their contributions to genetic variance and genomic predictions for 23 beef production traits in 1476 beef cattle. We cataloged the expression of 25,530 annotated genes, 28,533 novel long non-coding RNAs (lncRNAs), 215,754 AS events, and 3,093,058 A-to-I RNA-editing sites. Integrating transcriptome BodyMap with 23 beef production traits, we found lncRNAs influenced traits like rib-eye area and carcass length, while RNA editing associated with chunk roll weight and daily gain. We observed trait-relevant tissues between different stages, including the differential expressed genes of cerebellum, longissimus muscle, and testis between newborn and adult stages are more relevant to beef production traits. The tissue-specific genes and development-associated genes in several tissues could improve the reliability of genomic prediction in beef production traits. We developed Cattle BodyMap Transcriptome Database (https://cattlegenomics.online/cattle_bodymap) to retrieve, analyze, and visualize gene expression, lncRNA, splicing and RNA editing data. Our results demonstrated the potential of using transcriptome data as a valuable resource for genomic selection and breeding programs in beef cattle. Additionally, our transcriptome BodyMap serves as a valuable resource for biological interpretation, functional validation, and genomic improvement in livestock.</p>","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":7.9,"publicationDate":"2026-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148393097","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":"Real-time Targeted Enrichment in Single-cell Long-read Sequencing.","authors":"Xiang Jennie Li, Careen Foord, Andrey D Prjibelski, Natan Belchikov, Anoushka Joglekar, Justine Hsu, Julien Jarroux, Alexandru I Tomescu, Wen Hu, Hagen U Tilgner","doi":"10.1093/gpbjnl/qzag051","DOIUrl":"https://doi.org/10.1093/gpbjnl/qzag051","url":null,"abstract":"<p><p>The vast majority of multi-exonic genes are alternatively spliced, generating diverse and cell-type-specific isoforms exhibiting functional differences. To better capture this heterogeneity using single-cell long-read sequencing data, we previously developed an exome-probe-based approach to enrich for exonic reads of target genes. While effective, this procedure is time-consuming and expensive. Real-time targeting offers a more cost-efficient solution for selectively sequencing reads of interest. Here, we performed real-time enrichment of exonic sequences of single-cell long reads by targeting spliced transcripts from 3377 genes implicated in brain functions and related diseases. Our approach increased the total number of spliced on-target reads to up to 1.82 times the control level. Notably, targeting lowly expressed subsets yielded spliced on-target reads 1.39 to 1.89 times the control. While these gains do not rival those achieved using chemical probe-based enrichment, they are sufficient to significantly enhance the power of downstream statistical analyses, such as testing for cell-type-specific isoform abundance. Specifically, compared to naïve single-cell long-read sequencing, our approach yielded 2.42 times as many genes with significant differences in isoform usage between neurons and glia. Real-time targeting confirms cell-type-specific splicing in two early Mapt exons and newly reveals such events in > 100 genes, including Bak1 and Atp8a1. Overall, our findings highlight real-time targeting as a versatile method for enhancing resolution in detecting differential isoform usage across cell types in single-cell long-read data, offering the potential to obtain a fuller view of cellular isoform diversity.</p>","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":7.9,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148371369","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":"Decoding RNA N6-Methyladenosine Methylome of Wheat Using Machine Learning and Nanopore Direct RNA Sequencing.","authors":"Minggui Song, Jing Yang, Songyu Liu, Yuhang Ma, Tingrui Shi, Shang Xie, Jingjing Zhai, Zenglin Li, Chuang Ma","doi":"10.1093/gpbjnl/qzag053","DOIUrl":"https://doi.org/10.1093/gpbjnl/qzag053","url":null,"abstract":"<p><p>Nanopore direct RNA sequencing (DRS) enables transcriptome-wide detection of N6-methyladenosine (m6A), a pivotal RNA modification that regulates plant growth, development, and stress responses, at single-base resolution. However, existing Nanopore DRS-based m6A detection tools are often trained on ionic current signals from synthetic RNAs or model species, which limits their applicability to species with complex or polyploid genomes. Here, we present CatMOD, an ensemble machine learning framework for accurate m6A detection in plant DRS data that integrates complementary ionic current signal and non-signal features. CatMOD incorporates an evidence-based positive sampling strategy to improve generalizability across diverse plant species. Applied to Nanopore DRS data from seedlings of allohexaploid wheat (Triticum aestivum L.), CatMOD generated the first genome-wide, single-base resolution m6A atlas for this species. The atlas revealed variation in the number of predicted m6A sites among A, B, and D subgenomes within 1:1:1 homoeologous triads. Furthermore, subgenome-balanced m6A patterns were potentially associated with tissue-dependent expression plasticity of these triads. This study provides the first single-base resolution m6A atlas for wheat and establishes a scalable Nanopore DRS-based computational framework for epitranscriptome analysis in wheat and other polyploid species.</p>","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":7.9,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148371427","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":"Advancing Functional Transcriptomics in Zebrafish with High-accuracy Full-length RNA Sequencing.","authors":"Monika Kwiatkowska, Tomasz Mądry, Marta Blangiewicz, Silvia Carbonell-Sala, Roderic Guigó, Barbara Uszczynska-Ratajczak","doi":"10.1093/gpbjnl/qzag056","DOIUrl":"https://doi.org/10.1093/gpbjnl/qzag056","url":null,"abstract":"<p><p>Zebrafish (Danio rerio) is a powerful vertebrate model organism with strong genetic and physiological similarity to humans, yet its use in large-scale transcriptomic research remains constrained by incomplete gene annotations, inefficient ribodepletion methods, and limited transcript-level resolution. To tackle these challenges, we applied CapTrap-seq, a platform-agnostic long-read RNA sequencing approach combining cap-trapping with oligo(dT) priming to selectively capture 5'-capped, full-length transcripts, to zebrafish developmental stages and adult tissues. We further introduce a size-selection step that substantially improves recovery of longer RNA molecules without compromising quantitative accuracy. Benchmarking against the template-switching oligo (TSO) approach demonstrated that CapTrap-seq enables accurate and reproducible transcript reconstruction in a non-mammalian system without requiring external ribodepletion or validation resources. Comparative analysis across multiple long-read catalogues showed that CapTrap-seq detected the largest number of biologically and clinically relevant genes, including oxidative phosphorylation, cardiac, and Online Mendelian Inheritance in Man (OMIM) disease genes, while revealing extensive isoform diversity absent from current annotations. Analysis of the carmn and dancr lncRNA loci further demonstrated the ability to resolve complex splicing landscapes, uncovering novel full-length isoforms with distinct domain architectures not represented in existing zebrafish reference annotations. CapTrap-seq thus emerges as a robust, genome-agnostic framework for high-quality transcriptome characterisation in zebrafish and other under-annotated species, with broad implications for functional genomics and translational research.</p>","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":7.9,"publicationDate":"2026-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148354984","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}