Genomics, proteomics & bioinformatics最新文献

{"title":"PlateletBase: A Comprehensive Knowledgebase for Platelet Research and Disease Insights.","authors":"Huaichao Luo, Changchun Wu, Sisi Yu, Hanxiao Ren, Xing Yin, Ruiling Zu, Lubei Rao, Peiying Zhang, Xingmei Zhang, Ruohao Wu, Ping Leng, Kaijiong Zhang, Qi Peng, Bangrong Cao, Rui Qin, Hulin Wei, Jianlin Qiao, Shanling Xu, Qun Yi, Yang Zhang, Jian Huang, Dongsheng Wang","doi":"10.1093/gpbjnl/qzaf031","DOIUrl":"10.1093/gpbjnl/qzaf031","url":null,"abstract":"<p><p>Platelets are vital in many pathophysiological processes, yet there is a lack of a comprehensive resource dedicated specifically to platelet research. To fill this gap, we have developed PlateletBase, a knowledge base aimed at enhancing the understanding and study of platelets and related diseases. Our team retrieved information from various public databases, specifically extracting and analyzing RNA sequencing (RNA-seq) data from 3711 samples across 41 different conditions available on the National Center for Biotechnology Information (NCBI). PlateletBase offers six analytical and visualization tools, enabling users to perform gene similarity analysis, pair correlation, multi-correlation, expression ranking, clinical information association, and gene annotation for platelets. The current version of PlateletBase includes 10,278 genomic entries, 31,758 transcriptomic entries, 4869 proteomic entries, 2614 omics knowledge entries, 1833 drugs, 97 platelet resources, 438 diseases/traits, and six analysis modules. Each entry has been carefully curated and supported by experimental evidence. Additionally, PlateletBase features a user-friendly interface designed for efficient querying, manipulation, browsing, visualization, and analysis of detailed platelet protein and gene information. The case studies on gray platelet syndrome and angina pectoris demonstrate that PlateletBase is a suitable tool for identifying diagnostic biomarkers and exploring disease mechanisms, thereby advancing research in platelet functionality. PlateletBase is accessible at http://plateletbase.clinlabomics.org.cn/.</p>","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":7.9,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12342366/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144028363","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":"Clonal Hematopoietic Mutations in Plasma Cell Disorders: Clinical Subgroups and Shared Pathogenesis.","authors":"Xuezhu Wang, Liping Zuo, Yanying Yu, Xinyi Xiong, Jian Xu, Bing Qiao, Jia Chen, Hao Cai, Qi Yan, Hongxiao Han, Xin-Xin Cao, Jun Deng, Chunyan Sun, Jian Li","doi":"10.1093/gpbjnl/qzaf027","DOIUrl":"10.1093/gpbjnl/qzaf027","url":null,"abstract":"<p><p>Plasma cell disorders (PCDs) are marked by the clonal proliferation of abnormal plasma cells and bone marrow plasma cells (BMPCs), causing various clinical complications. These PCDs include subtypes with distinct clinical features. Multiple myeloma (MM) and monoclonal gammopathy of undetermined significance (MGUS) are more common and relatively well-studied. In contrast, primary light-chain amyloidosis (AL) and POEMS syndrome (POEMS) are rare and remain less understood. To investigate the role of clonal hematopoietic (CH) mutations and potential interconnections in these diseases, we sequenced CH mutations in lymphoid and myeloid lineages, as well as myeloma driver gene mutations, in BMPCs from affected patients. Recurrent lymphoid CH mutations (in FAT1, KMT2D, MGA, and SYNE1) and myeloma driver gene mutations (in ZFHX3 and DIS3) were found in the dominant clonal and subclonal plasma cell populations. These moderately aging-associated lymphoid CH mutations had a higher burden in MM than in AL or POEMS. Binary matrix factorization of these mutations revealed the subgroups associated with progression-free survival (PFS) (observed in MM, AL, and POEMS), age at diagnosis (in AL and POEMS), serum differential free light chain (dFLC) levels, plasma cell burden (in AL), and serum vascular endothelial growth factor (VEGF) levels (in POEMS). Moreover, the poor PFS associated with MGA or SYNE1 mutations was confirmed across MM, AL, and POEMS. CH mutations partially explained the shared pathogenesis of MM, AL, POEMS, and MGUS, and helped identify patient subgroups with specific clinical features.</p>","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":7.9,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12342758/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143733745","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":"Cell-free DNA Fragmentomics Assay to Discriminate the Malignancy of Breast Nodules and Evaluate Treatment Response.","authors":"Jiaqi Liu 刘嘉琦, Yalun Li 李亚伦, Wanxiangfu Tang 唐皖湘夫, Tianyi Qian 钱天一, Lijun Dai 代丽君, Ziqi Jia 贾梓淇, Heng Cao 曹恒, Chenghao Li 李成浩, Yuchen Liu 刘煜琛, Yansong Huang 黄岩松, Jiang Wu 吴疆, Dongxu Ma 马东旭, Guangdong Qiao 乔广东, Hua Bao 包华, Shuang Chang 常双, Dongqin Zhu 朱冬琴, Shanshan Yang 杨珊珊, Xuxiaochen Wu 吴徐晓辰, Xue Wu 吴雪, Hengyi Xu 徐恒毅, Hongyan Chen 陈洪岩, Yang Shao 邵阳, Xiang Wang 王翔, Zhihua Liu 刘芝华, Jianzhong Su 苏建忠","doi":"10.1093/gpbjnl/qzaf028","DOIUrl":"10.1093/gpbjnl/qzaf028","url":null,"abstract":"<p><p>The fragmentomics-based cell-free DNA (cfDNA) assays have recently illustrated prominent abilities to identify various cancers from non-conditional healthy controls, while their accuracy for identifying early-stage cancers from benign lesions with inconclusive imaging results remains uncertain. Especially for breast cancer, current imaging-based screening methods suffer from high false positive rates for women with breast nodules, leading to unnecessary biopsies, which add to discomfort and healthcare burden. Here, we enrolled 613 female participants in this multi-center study and demonstrated that cfDNA fragmentomics (cfFrag) is a robust non-invasive biomarker for breast cancer using whole-genome sequencing. Among the multimodal cfFrag profiles, the fragment size ratio (FSR), fragment size distribution (FSD), and copy number variation (CNV) show more distinguishing ability than Griffin, motif breakpoint (MBP), and neomer. The cfFrag model using the optimal three fragmentomics features discriminated early-stage breast cancer from benign nodules, even at a low sequencing depth (3×). Notably, it demonstrated a specificity of 94.1% in asymptomatic healthy women at a 90% sensitivity for breast cancer. Moreover, we comprehensively showcased the clinical utility of the cfFrag model in predicting patient responses to neoadjuvant chemotherapy (NAC) and its enhanced performance when combined with multimodal features, including radiological results [area under the curve (AUC) = 0.93-0.94] and cfDNA methylation features (AUC = 0.96).</p>","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":7.9,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12321295/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143784657","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":"Resolving Leukemia Heterogeneity and Lineage Aberrations with HematoMap.","authors":"Yuting Dai 代雨婷, Wen Ouyang 欧阳文, Wen Jin 金雯, Fan Zhang 张凡, Wenyan Cheng 程雯艳, Jianfeng Li 李剑峰, Shuo He 何硕, Junqi Zong 宗俊圻, Shijia Cao 曹诗佳, Chenxin Zhou 周晨馨, Junchen Luo 骆俊辰, Gang Lv 吕纲, Jinyan Huang 黄金艳, Hai Fang 方海, Xiaojian Sun 孙晓建, Kankan Wang 王侃侃, Saijuan Chen 陈赛娟","doi":"10.1093/gpbjnl/qzaf005","DOIUrl":"10.1093/gpbjnl/qzaf005","url":null,"abstract":"<p><p>Precise mapping of leukemic cells onto the known hematopoietic hierarchy is important for understanding the cell-of-origin and mechanisms underlying disease initiation and development. However, this task remains challenging because of the high interpatient and intrapatient heterogeneity of leukemia cell clones as well as the differences that exist between leukemic and normal hematopoietic cells. Using single-cell RNA sequencing (scRNA-seq) data with a curated clustering approach, we constructed a comprehensive reference hierarchy of normal hematopoiesis. This reference hierarchy was accomplished through multistep clustering and annotating over 100,000 bone marrow mononuclear cells derived from 25 healthy donors. We further employed the cosine distance algorithm to develop a likelihood score to determine the similarities of leukemic cells to their putative normal counterparts. Using our scoring strategies, we mapped the cells of acute myeloid leukemia (AML) and B cell precursor acute lymphoblastic leukemia (BCP-ALL) samples to their corresponding counterparts. The reference hierarchy also facilitated bulk RNA sequencing (RNA-seq) analysis, enabling the development of a least absolute shrinkage and selection operator (LASSO) score model to reveal subtle differences in lineage aberrancy within AML or BCP-ALL patients. To facilitate interpretation and application, we established an R-based package (HematoMap) that offers a fast, convenient, and user-friendly tool for identifying and visualizing lineage aberrations in leukemia from scRNA-seq and bulk RNA-seq data. Our tool provides curated resources and data analytics for understanding leukemogenesis, with the potential to enhance leukemia risk stratification and personalized treatments. The HematoMap is available at https://github.com/NRCTM-bioinfo/HematoMap.</p>","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":7.9,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12343003/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143412118","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":"Reprogramming of RNA m6A Modification Is Required for Acute Myeloid Leukemia Development.","authors":"Weidong Liu, Yuhua Wang, Shuxin Yao, Guoqiang Han, Jin Hu, Rong Yin, Fuling Zhou, Ying Cheng, Haojian Zhang","doi":"10.1093/gpbjnl/qzae049","DOIUrl":"10.1093/gpbjnl/qzae049","url":null,"abstract":"<p><p>Hematopoietic homeostasis is maintained by hematopoietic stem cells (HSCs), and it is tightly controlled at multiple levels to sustain the self-renewal capacity and differentiation potential of HSCs. Dysregulation of self-renewal and differentiation of HSCs leads to the development of hematologic diseases, including acute myeloid leukemia (AML). Thus, understanding the underlying mechanisms of HSC maintenance and the development of hematologic malignancies is one of the fundamental scientific endeavors in stem cell biology. N6-methyladenosine (m6A) is a common modification in mammalian messenger RNAs (mRNAs) and plays important roles in various biological processes. In this study, we performed a comparative analysis of the dynamics of the RNA m6A methylome of hematopoietic stem and progenitor cells (HSPCs) and leukemia-initiating cells (LICs) in AML. We found that RNA m6A modification regulates the transition of long-term HSCs into short-term HSCs and determines the lineage commitment of HSCs. Interestingly, m6A modification leads to reprogramming that promotes cellular transformation during AML development, and LIC-specific m6A targets are recognized by different m6A readers. Moreover, the very long chain fatty acid transporter ATP-binding cassette subfamily D member 2 (ABCD2) is a key factor that promotes AML development, and deletion of ABCD2 damages clonogenic ability, inhibits proliferation, and promotes apoptosis of human leukemia cells. This study provides a comprehensive understanding of the role of m6A in regulating cell state transition in normal hematopoiesis and leukemogenesis, and identifies ABCD2 as a key factor in AML development.</p>","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":7.9,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12373641/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141447874","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":"Whole-genome Sequencing Association Analysis of Quantitative Platelet Traits in A Large Cohort of β-thalassemia.","authors":"Xingmin Wang, Qianqian Zhang, Xianming Chen, Yushan Huang, Wei Zhang, Liuhua Liao, Xinhua Zhang, Binbin Huang, Yueyan Huang, Yuhua Ye, Mengyang Song, Jinquan Lao, Juanjuan Chen, Xiaoqin Feng, Xingjiang Long, Zhixiang Liu, Weijian Zhu, Lian Yu, Chengwu Fan, Deguo Tang, Tianyu Zhong, Mingyan Fang, Caiyun Li, Chao Niu, Li Huang, Bin Lin, Xiaoyun Hua, Xin Jin, Zilin Li, Xiangmin Xu","doi":"10.1093/gpbjnl/qzae065","DOIUrl":"10.1093/gpbjnl/qzae065","url":null,"abstract":"<p><p>Platelets act as a crucial indicator for monitoring hypercoagulability and thrombosis and a key target for pharmacological intervention. Genotype-phenotype association studies have confirmed that platelet traits are quantitatively regulated by multiple genes. However, there is currently a lack of genetic studies on the heterogeneity of platelet traits in β-thalassemia under a hypercoagulable state. Here, we studied the phenotypic heterogeneity of platelet count (PLT) and mean platelet volume (MPV) in a cohort of 1020 β-thalassemia patients. We further performed a functionally informed whole-genome sequencing (WGS) association analysis of common variants and rare variants for PLT and MPV in 916 patients through integrative analysis of WGS data and functional annotation data. Extreme phenotypic heterogeneity of platelet traits was observed in β-thalassemia patients. Additionally, the common variant-based gene-level analysis identified RNF144B as a novel gene associated with MPV. The rare variant analysis identified several novel associations in both coding and noncoding regions, including missense rare variants of PPP2R5C associated with PLT and missense rare variants of TSSK1B associated with MPV. In conclusion, this comprehensive and systematic whole-genome scan of platelet traits in the β-thalassemia cohort reveals the specific genetic regulation of platelet traits in the context of β-thalassemia, providing potential targets for intervention.</p>","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":7.9,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12373638/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142335112","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":"HemaScope: A Tool for Analyzing Single-cell and Spatial Transcriptomics Data of Hematopoietic Cells.","authors":"Zhenyi Wang, Yuxin Miao, Hongjun Li, Wenyan Cheng, Minglei Shi, Gang Lv, Yating Zhu, Junyi Zhang, Tingting Tan, Jin Gu, Michael Q Zhang, Jianfeng Li, Hai Fang, Zhu Chen, Saijuan Chen","doi":"10.1093/gpbjnl/qzaf002","DOIUrl":"10.1093/gpbjnl/qzaf002","url":null,"abstract":"<p><p>Single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) techniques hold great value in evaluating the heterogeneity and spatial characteristics of hematopoietic cells within tissues. These two techniques are highly complementary, with scRNA-seq offering single-cell resolution and ST retaining spatial information. However, there is an urgent demand for well-organized and user-friendly toolkits capable of handling single-cell and spatial information. Here, we present HemaScope, a specialized bioinformatics toolkit featuring modular designs to analyze scRNA-seq and ST data generated from hematopoietic cells. It enables users to perform quality control, basic analysis, cell atlas construction, cellular heterogeneity exploration, and dynamical examination on scRNA-seq data. Also, it can perform spatial analysis and microenvironment analysis on ST data. Meanwhile, HemaScope takes into consideration hematopoietic cell-specific features, including lineage affiliation evaluation, cell cycle prediction, and marker gene collection. To enhance the user experience, we have deployed the toolkit in user-friendly forms: HemaScopeR (an R package), HemaScopeCloud (a web server), HemaScopeDocker (a Docker image), and HemaScopeShiny (a graphical interface). In case studies, we employed it to construct a cell atlas of human bone marrow, analyze age-related changes, and identify acute myeloid leukemia cells in mice. Moreover, we characterized the microenvironments in angioimmunoblastic T cell lymphoma and primary central nervous system lymphoma, elucidating tumor boundaries. HemaScope is freely available at https://zhenyiwangthu.github.io/HemaScope_Tutorial/.</p>","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":7.9,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12374577/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143043874","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":"HemAtlas: A Multi-omics Hematopoiesis Database.","authors":"Zhixin Kang, Tongtong Zhu, Dong Zou, Mengyao Liu, Yifan Zhang, Lu Wang, Zhang Zhang, Feng Liu","doi":"10.1093/gpbjnl/qzaf026","DOIUrl":"10.1093/gpbjnl/qzaf026","url":null,"abstract":"<p><p>Advancements in high-throughput omics technologies have facilitated a systematic exploration of crucial hematopoietic organs across diverse species. A thorough understanding of hematopoiesis in vivo and facilitation of generating functional hematopoietic stem and progenitor cells (HSPCs) in vitro necessitate a comprehensive hematopoietic cross-stage developmental landscape across species. To address this need, we developed HemAtlas, a platform designed for the systematic mapping of hematopoiesis both in vivo and in vitro. HemAtlas features detailed analyses of multi-omics datasets from humans, mice, zebrafish, and HSPC in vitro culture systems. Utilizing literature curation and data normalization, HemAtlas integrates various functional modules, allowing interactive exploration and visualization of any collected omics data based on user-specific interests. Moreover, by applying a systematic and uniform integration method, we constructed organ-wide hematopoietic references for each species with manually curated cell annotations, enabling a comprehensive decoding of cross-stage developmental hematopoiesis at the organ level. Of particular significance are three distinctive functions - single-cell cross-stage, cross-species, and cross-model analyses - that HemAtlas employs to elucidate the hematopoietic development in zebrafish, mice, and humans, and to offer guidance on the generation of HSPCs in vitro. Simultaneously, HemAtlas incorporates a comprehensive map of HSPC cross-stage development to reveal HSPC stage-specific properties. Taken together, HemAtlas serves as a crucial resource to advance our understanding of hematopoiesis and is available at https://ngdc.cncb.ac.cn/hematlas/.</p>","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":7.9,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12374576/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143665771","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":"Pathogen Adaptation of HLA Alleles and Its Correlation with Autoimmune Diseases in the Han Chinese.","authors":"Shuai Liu 刘帅, Yanyan Li 李燕燕, Tingrui Song 宋廷瑞, Jingjing Zhang 张晶晶, Peng Zhang 张鹏, Huaxia Luo 罗华夏, Sijia Zhang 张斯佳, Yiwei Niu 牛仪伟, Tao Xu 徐涛, Shunmin He 何顺民","doi":"10.1093/gpbjnl/qzaf038","DOIUrl":"10.1093/gpbjnl/qzaf038","url":null,"abstract":"<p><p>Human leukocyte antigen (HLA) genes play a crucial role in the adaptation of human populations to the dynamic pathogenic environment. Despite their significance, investigating the pathogen-driven evolution of HLAs and its implications for autoimmune diseases presents considerable challenges. Here, we genotyped over 20 HLA genes at 3-field resolution in 8278 individuals from diverse ethnic backgrounds, including 4013 unrelated Han Chinese individuals. We focused on the adaptation of HLAs in the Han Chinese population by analyzing their binding affinity for various pathogens, and explored the potential correlations between pathogen adaptation and autoimmune diseases. Our findings reveal that specific HLA alleles like HLA-DRB1*07:01 and HLA-DQB1*06:01 confer strong pathogen adaptability at the sequence level, notably for Corynebacterium diphtheriae and Bordetella pertussis. Additionally, alleles like HLA-C*03:02 demonstrate adaptive selection against pathogens like Mycobacterium tuberculosis and coronavirus at the gene expression level. Simultaneously, the aforementioned HLA alleles are closely related to some autoimmune diseases such as multiple sclerosis. These exploratory discoveries shed light on the intricate coevolutionary relationships between pathogen adaptation and autoimmune diseases in the human population. These efforts led to an HLA database at http://bigdata.ibp.ac.cn/HLAtyping, aiding searches for HLA allele frequencies across populations.</p>","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":7.9,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12368854/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144060419","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":"Integrated Computational and Functional Screening Identifies G9a Inhibitors for SETD2-mutant Leukemia.","authors":"Ya Zhang, Mengfang Xia, Zhenyi Yi, Pinpin Sui, Xudong He, Liping Wang, Qiyi Chen, Hong-Hu Zhu, Gang Huang, Qian-Fei Wang","doi":"10.1093/gpbjnl/qzaf035","DOIUrl":"10.1093/gpbjnl/qzaf035","url":null,"abstract":"<p><p>SETD2, a frequently mutated epigenetic tumor suppressor gene in acute leukemia, is associated with chemotherapy resistance and poor patient outcomes. To explore potential therapeutics for SETD2-mutant leukemia, we employed an integrated approach combining computational prediction with epigenetic compound library screening. This approach identified G9a inhibitors as promising candidates, capable of reversing gene expression signatures associated with Setd2 deficiency and selectively inhibiting SETD2-deficient cells. RNA sequencing analysis revealed that the G9a inhibitor significantly downregulated Myc and Myc-regulated genes involved in translation, DNA replication, and G1/S transition in Setd2-mutant cells. Further chromatin immunoprecipitation sequencing analysis showed that G9a inhibition reduced H3K9me2 levels at the long non-coding RNA Mir100hg locus, coinciding with specific upregulation of the embedded microRNA let-7a-2 in Setd2-mutant cells. Given the established role of let-7a in MYC suppression, these findings suggest a potential mechanism by which G9a inhibitors induce MYC downregulation in SETD2-mutant leukemia. Additionally, correlation analysis between computational predictions and phenotypic outcomes highlighted the MYC signature as a key predictor of drug efficacy. Collectively, our study identifies G9a inhibitors as a promising therapeutic avenue for SETD2-mutant leukemia and provides novel insights into refining drug prediction strategies.</p>","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":7.9,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12373973/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144039579","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}