{"title":"Proteome and Phosphoproteome of Tomato Fruit Identify REDUCED CHLOROPLAST COVERAGE 1a as A Ripening Regulator.","authors":"Jinjuan Tan, Zhongjing Zhou, Hanqian Feng, Jiateng Zhang, Ruikai Zhang, Zhongkai Chen, Yujie Niu, Fangyu Liu, Zhiping Deng","doi":"10.1093/gpbjnl/qzaf050","DOIUrl":"https://doi.org/10.1093/gpbjnl/qzaf050","url":null,"abstract":"<p><p>Fruit ripening in tomato (Solanum lycopersicum) has been extensively studied at the transcriptomics level. However, comprehensive profiling of the tomato fruit proteome and phosphoproteome remains limited. In this study, we performed large-scale proteome and phosphoproteome profiling of tomato (Ailsa Craig) fruits across five ripening stages using tandem mass tags (TMT)-based quantitative proteomics. Our analysis quantified over 8800 proteins and 20,000 high-confidence phosphorylation sites. Ripening-associated phosphorylation and dephosphorylation events were identified in diverse ripening regulators, including transcription factors, ethylene biosynthesis and signaling proteins, and epigenetic modifiers. Weighted gene co-expression network analysis (WGCNA) revealed a tetratricopeptide repeat protein, REDUCED CHLOROPLAST COVERAGE 1a (REC1a), as a key regulator of fruit ripening. Parallel reaction monitoring (PRM)-based targeted proteomic analysis validated the expression profiles of REC1a and its three phosphorylation sites. Clustered regularly interspaced short palindromic repeats (CRISPR)-CRISPR-associated protein 9 (Cas9)-mediated knockout of REC1a resulted in reduced lycopene accumulation and slower chlorophyll degradation, highlighting its role in the chloroplast-to-chromoplast transition, which is critical for fruit pigmentation during ripening. Quantitative proteomic analyses of rec1a mutants demonstrated reduced levels of Clp proteases and chaperones, proteins known to regulate plastid transitions. Additionally, co-immunoprecipitation and split-luciferase complementation assays revealed that REC1a interacts with the eukaryotic translation initiation factor subunits eIF2α and eIF2Bβ, suggesting its role in regulating protein synthesis during ripening. This study provides the most comprehensive quantitative proteome and phosphoproteome atlas of tomato fruits to date and identifies REC1a as a novel regulator of plastid development, offering new insights into the molecular mechanisms underlying fruit ripening.</p>","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144259707","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}
Zhiyong Wang, Kaijun Liu, Haibing Yuan, Shuhan Duan, Yunhui Liu, Lintao Luo, Xiucheng Jiang, Shijia Chen, Lanhai Wei, Renkuan Tang, Liping Hu, Jing Chen, Xiangping Li, Qingxin Yang, Yuntao Sun, Qiuxia Sun, Yuguo Huang, Haoran Su, Jie Zhong, Hongbing Yao, Libing Yun, Jianbo Li, Junbao Yang, Yan Cai, Hong Deng, Jiangwei Yan, Bofeng Zhu, Kun Zhou, Shengjie Nie, Chao Liu, Mengge Wang, Guanglin He
{"title":"YanHuang Paternal Genomic Resource Suggested A Weakly-Differentiated Multi-Source Admixture Model for the Formation of Han's Founding Ancestral Lineages.","authors":"Zhiyong Wang, Kaijun Liu, Haibing Yuan, Shuhan Duan, Yunhui Liu, Lintao Luo, Xiucheng Jiang, Shijia Chen, Lanhai Wei, Renkuan Tang, Liping Hu, Jing Chen, Xiangping Li, Qingxin Yang, Yuntao Sun, Qiuxia Sun, Yuguo Huang, Haoran Su, Jie Zhong, Hongbing Yao, Libing Yun, Jianbo Li, Junbao Yang, Yan Cai, Hong Deng, Jiangwei Yan, Bofeng Zhu, Kun Zhou, Shengjie Nie, Chao Liu, Mengge Wang, Guanglin He","doi":"10.1093/gpbjnl/qzaf049","DOIUrl":"https://doi.org/10.1093/gpbjnl/qzaf049","url":null,"abstract":"<p><p>The revolution in large-scale human genomics and advancements in statistical methods have profoundly refined our understanding of genetic diversity and structure within human populations. Y-chromosome variations, with their distinct evolutionary characteristics, play crucial roles in reconstructing the origins and interactions of ancient East Asian paternal lineages. We launched the YanHuang cohort employing a high-resolution capture sequencing panel to explore the evolutionary trajectory of Han Chinese, one of the world's largest ethnic groups. We generated paternal genomic data for 5020 Han Chinese individuals across 29 Chinese administrative regions. We observed that multiple founding paternal lineages originating from ancient western Eurasia, Siberia, and East Asia contributed significantly to the Han Chinese gene pool. We identified fine-scale paternal genetic structures shaped by interactions among ancient populations and geographic barriers like the Qinling-Huaihe line and the Nanling Mountains. This structure reflects both isolation-enhanced and admixture-driven genetic differentiation, underscoring the complexity of Han Chinese genomic diversity. We observed a strong correlation between the frequency of multiple founding lineages and subsistence-related ancestral sources, including western pastoralists, Holocene Mongolian Plateau populations, and ancient East Asians. This relationship highlights the impact of ancient migrations and admixture on Chinese paternal genomic diversity. We introduce the Weakly-Differentiated Multi-Source Admixture model to clarify the intricate interactions among multiple ancestral sources influencing the Han Chinese paternal landscape. This study provides a comprehensive uniparental genomic resource from the YanHuang cohort, proposes a novel admixture model, and delineates the complex genomic landscape shaped by ancient herders, hunter-gatherers, and farmers integral to Han Chinese ancestry.</p>","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144228061","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}
Fuhong He, Zhaojun Zhang, Xiangdong Fang, Qian-Fei Wang
{"title":"Biomedical Big Data and Artificial Intelligence in Blood.","authors":"Fuhong He, Zhaojun Zhang, Xiangdong Fang, Qian-Fei Wang","doi":"10.1093/gpbjnl/qzaf043","DOIUrl":"10.1093/gpbjnl/qzaf043","url":null,"abstract":"","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12123044/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144015145","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":"Unveiling Neonatal Pneumonia Microbiome by High-Throughput Sequencing and Droplet Culturomics.","authors":"Zerui Wang, Xin Cheng, Yibin Xu, Zhiyi Wang, Liyan Ma, Caiming Li, Shize Jiang, Yuchen Li, Shuilong Guo, Wenbin Du","doi":"10.1093/gpbjnl/qzaf047","DOIUrl":"https://doi.org/10.1093/gpbjnl/qzaf047","url":null,"abstract":"<p><p>Neonatal pneumonia is a leading cause of infant mortality worldwide; however, a lack of microbial profiling, especially of low-abundance species, makes accurate diagnosis challenging. Traditional methods can fail to capture the complexity of the neonatal respiratory microbiota, thereby obscuring its role in disease progression. We describe a novel approach that combines high-throughput sequencing with droplet-based microfluidic cultivation to investigate microbiome shifts in neonates with pneumonia. Using 16S ribosomal RNA (rRNA) gene sequencing of 71 pneumonia cases and 49 controls, we identified 1009 genera, including 930 low-abundance taxa, which showed significant compositional differences between groups. Linear Discriminant Analysis Effect Size analysis identified key pneumonia-associated genera, such as Streptococcus, Rothia, and Corynebacterium. Droplet-based cultivation recovered 299 strains from 94 taxa, including rare species and ESKAPE pathogens, thereby supporting targeted antimicrobial management. Host-pathogen interaction assays showed that Rothia and Corynebacterium induced inflammation in lung epithelial cells, likely via dysregulation of the PI3K-Akt pathway. Integrating these marker taxa with clinical factors, such as gestational age and delivery type, offers the potential for precise diagnosis and treatment. The recovery of diverse species can support the construction of a biobank of neonatal respiratory microbiota to advance mechanistic studies and therapeutic strategies.</p>","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144176288","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}
Chen Wang, Hong Zhao, Hongkui Zhang, Sijie Sun, Yongbiao Xue
{"title":"PSIA: A Comprehensive Knowledgebase of Plant Self-Incompatibility.","authors":"Chen Wang, Hong Zhao, Hongkui Zhang, Sijie Sun, Yongbiao Xue","doi":"10.1093/gpbjnl/qzaf046","DOIUrl":"https://doi.org/10.1093/gpbjnl/qzaf046","url":null,"abstract":"<p><p>Self-incompatibility (SI) is an important genetic mechanism in angiosperms that prevents inbreeding and promotes outcrossing, with significant implications for crop breeding, including genetic diversity, hybrid seed production, and yield optimization. In eudicots, SI is typically governed by a single S-locus containing tightly linked pistil and pollen S-determinant genes. Despite major advances in SI research, a centralized, comprehensive resource for SI-related genomic data remains lacking. To address this gap, we developed the Plant Self-Incompatibility Atlas (PSIA), a systematically curated knowledgebase providing an extensive compilation of plant SI, including genomic resources for SI species, S gene annotations, molecular mechanisms, phylogenetic relationships, and comparative genomic analyses. The current release of PSIA includes over 500 genome assemblies from 469 SI species. Using known S genes as queries, we manually identified and rigorously curated 3700 S genes. PSIA provides detailed S-locus information from assembled SI species and offers an interactive platform for browsing, BLAST searches, S gene analysis, and data retrieval. Additionally, PSIA serves as a unique platform for comparative genomic studies of S-loci, facilitating exploration of the dynamic processes underlying the origin, loss, and regain of SI. As a comprehensive and user-friendly resource, PSIA will greatly advance our understanding of angiosperm SI and serve as a valuable tool for crop breeding and hybrid seed production. PSIA is freely available at http://www.plantsi.cn.</p>","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144113067","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":"GDBIG: A Pioneering Birth Cohort Genomic Platform Facilitating Intergenerational Genetic Research.","authors":"Shujia Huang, Chengrui Wang, Mingxi Huang, Jinhua Lu, Jian-Rong He, Shanshan Lin, Siyang Liu, Huimin Xia, Xiu Qiu","doi":"10.1093/gpbjnl/qzaf045","DOIUrl":"https://doi.org/10.1093/gpbjnl/qzaf045","url":null,"abstract":"<p><p>High-quality genome databases derived from large-scale, family-based birth cohorts are vital resources for investigating the genetic determinants of early-life traits and the impact of early-life environments on the health of both parents and offspring. Here, we established the genomic platform of the Born in Guangzhou Cohort Study (BIGCS), named the Genome Database of BIGCS (GDBIG), which represents the first birth cohort-based genomic database in China and is designed to facilitate intergenerational genetic research. Based on the phase I results of the BIGCS, GDBIG includes low-coverage (∼ 6.63×) whole genome sequencing (WGS) data and extensive pregnancy phenotypes from 4053 Chinese participants. These participants are from 30 of China's 34 administrative divisions, encompassing Han and 12 minority ethnic groups. Currently, GDBIG provides a range of services, including allele frequency queries for 56.23 million variants across two generations, a genotype imputation server featuring a high-quality family-based reference panel, and a genome-wide association study (GWAS) meta-analysis interface for various maternal and infant phenotypes. The GDBIG database addresses the lack of Asian birth cohort-based genomic resources and provides a valuable platform for conducting genetic analysis, accessible online or via application programming interfaces (API) at http://gdbig.bigcs.com.cn/.</p>","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144083031","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":"CircAge: A Comprehensive Resource for Aging-associated Circular RNAs Across Species and Tissues.","authors":"Xin Dong, Zhen Zhou, Yanan Wang, Ayesha Nisar, Shaoyan Pu, Longbao Lv, Yijiang Li, Xuemei Lu, Yonghan He","doi":"10.1093/gpbjnl/qzaf044","DOIUrl":"https://doi.org/10.1093/gpbjnl/qzaf044","url":null,"abstract":"<p><p>Circular RNAs (circRNAs) represent a novel class of RNA molecules characterized by a circular structure and enhanced stability. Emerging evidence indicates that circRNAs play pivotal regulatory roles in the aging process. Despite this, there is a lack of a systematic resource that integrates aging-associated circRNA data. Therefore, we developed a comprehensive database named CircAge, which encompasses 803 aging-related samples from 7 species and 24 tissue types. Through high-throughput sequencing, we also generated 47 new tissue samples from mice and rhesus monkeys. Integrating predictions from multiple bioinformatics tools, we identified over 529,856 unique circRNAs. Our data analysis revealed a general increase in circRNA expression levels with age, with approximately 23% of circRNAs demonstrating sequence conservation across species. The CircAge database systematically predicts potential interactions between circRNAs, microRNAs (miRNAs), and RNA-binding proteins (RBPs), and assesses the coding potential of circRNAs. This resource lays a foundation for elucidating the regulatory mechanisms of circRNAs in aging. As a comprehensive repository of aging-associated circRNAs, CircAge will significantly accelerate research in this field, facilitating the discovery of novel biomarkers and therapeutic targets for aging biology and developing diagnostic and therapeutic strategies for aging and age-related diseases. CircAge is publicly available at https://circage.kiz.ac.cn.</p>","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144033265","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}
Guohao Han 韩郭皓, Peng Yang 杨朋, Yongjin Zhang 张永进, Qiaowei Li 李巧伟, Xinhao Fan 范新浩, Ruipu Chen 陈锐朴, Chao Yan 闫超, Mu Zeng 曾木, Yalan Yang 杨亚岚, Zhonglin Tang 唐中林
{"title":"PIGOME: An Integrated and Comprehensive Multi-omics Database for Pig Functional Genomics Studies.","authors":"Guohao Han 韩郭皓, Peng Yang 杨朋, Yongjin Zhang 张永进, Qiaowei Li 李巧伟, Xinhao Fan 范新浩, Ruipu Chen 陈锐朴, Chao Yan 闫超, Mu Zeng 曾木, Yalan Yang 杨亚岚, Zhonglin Tang 唐中林","doi":"10.1093/gpbjnl/qzaf016","DOIUrl":"10.1093/gpbjnl/qzaf016","url":null,"abstract":"<p><p>In addition to being a major source of animal protein, pigs are an important model for studying development and diseases in humans. Over the past two decades, thousands of high-throughput sequencing studies in pigs have been performed using a variety of tissues from different breeds and developmental stages. However, multi-omics databases specifically designed for pig functional genomics research are still limited. Here, we present PIGOME, a user-friendly database of pig multi-omes. PIGOME currently contains seven types of pig omics datasets, including whole-genome sequencing (WGS), RNA sequencing (RNA-seq), microRNA sequencing (miRNA-seq), chromatin immunoprecipitation sequencing (ChIP-seq), assay for transposase-accessible chromatin sequencing (ATAC-seq), bisulfite sequencing (BS-seq), and methylated RNA immunoprecipitation sequencing (MeRIP-seq), from 6901 samples and 392 projects with manually curated metadata, integrated gene annotation, and quantitative trait locus information. Furthermore, various \"Explore\" and \"Browse\" functions have been established to provide user-friendly access to omics information. PIGOME implements several tools to visualize genomic variants, gene expression, and epigenetic signals of a given gene in the pig genome, enabling efficient exploration of spatiotemporal gene expression/epigenetic patterns, functions, regulatory mechanisms, and associated economic traits. Collectively, PIGOME provides valuable resources for pig breeding and is helpful for human biomedical research. PIGOME is available at https://pigome.com.</p>","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12122082/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143560323","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}
Tao Zhang 张韬, Yiyun Liu 刘依云, Xutong Guo 郭栩彤, Xinran Zhang 张欣然, Xinchang Zheng 郑欣畅, Mochen Zhang 张陌尘, Yiming Bao 鲍一明
{"title":"VISTA: A Tool for Fast Taxonomic Assignment of Viral Genome Sequences.","authors":"Tao Zhang 张韬, Yiyun Liu 刘依云, Xutong Guo 郭栩彤, Xinran Zhang 张欣然, Xinchang Zheng 郑欣畅, Mochen Zhang 张陌尘, Yiming Bao 鲍一明","doi":"10.1093/gpbjnl/qzae082","DOIUrl":"10.1093/gpbjnl/qzae082","url":null,"abstract":"<p><p>The rapid expansion of the number of viral genome sequences in public databases necessitates a scalable, universal, and automated preliminary taxonomic framework for comprehensive virus studies. Here, we introduce Virus Sequence-based Taxonomy Assignment (VISTA), a computational tool that employs a novel pairwise sequence comparison system and an automatic demarcation threshold identification framework for virus taxonomy. Leveraging physio-chemical property sequences, k-mer profiles, and machine learning techniques, VISTA constructs a robust distance-based framework for taxonomic assignment. Functionally similar to Pairwise Sequence Comparison (PASC), a widely used virus assignment tool based on pairwise sequence comparison, VISTA demonstrates superior performance by providing significantly improved separation for taxonomic groups, more objective taxonomic demarcation thresholds, greatly enhanced speed, and a wider application scope. We successfully applied VISTA to 38 virus families, as well as to the class Caudoviricetes. This demonstrates VISTA's scalability, robustness, and ability to automatically and accurately assign taxonomy to both prokaryotic and eukaryotic viruses. Furthermore, the application of VISTA to 679 unclassified prokaryotic virus genomes recovered from metagenomic data identified 46 novel virus families. VISTA is available as both a command line tool and a user-friendly web portal at https://ngdc.cncb.ac.cn/vista.</p>","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142635082","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}
Taoyu Chen 陈韬宇, Guoguo Tang 唐果菓, Tianhao Li 李天昊, Zhining Yanghong 杨宏芷宁, Chao Hou 侯超, Zezhou Du 杜泽州, Kaiqiang You 游铠强, Liwei Ma 马利伟, Tingting Li 李婷婷
{"title":"PhaSeDis: A Manually Curated Database of Phase Separation-disease Associations and Corresponding Small Molecules.","authors":"Taoyu Chen 陈韬宇, Guoguo Tang 唐果菓, Tianhao Li 李天昊, Zhining Yanghong 杨宏芷宁, Chao Hou 侯超, Zezhou Du 杜泽州, Kaiqiang You 游铠强, Liwei Ma 马利伟, Tingting Li 李婷婷","doi":"10.1093/gpbjnl/qzaf014","DOIUrl":"10.1093/gpbjnl/qzaf014","url":null,"abstract":"<p><p>Biomacromolecules form membraneless organelles through liquid-liquid phase separation in order to regulate the efficiency of particular biochemical reactions. Dysregulation of phase separation might result in pathological condensation or sequestration of biomolecules, leading to diseases. Thus, phase separation and phase separating factors may serve as drug targets for disease treatment. Nevertheless, such associations have not yet been integrated into phase separation-related databases. Therefore, based on MloDisDB, a database for membraneless organelle factor-disease associations previously developed by our lab, we constructed PhaSeDis, the phase separation-disease association database. We increased the number of phase separation entries from 52 to 185, and supplemented the evidence provided by the original articles verifying the phase separation nature of the factors. Moreover, we included the information of interacting small molecules with low-throughput or high-throughput evidence that might serve as potential drugs for phase separation entries. PhaSeDis strives to offer comprehensive descriptions of each entry, elucidating how phase separating factors induce pathological conditions via phase separation and the mechanisms by which small molecules intervene. We believe that PhaSeDis would be very important in the application of phase separation regulation in treating related diseases. PhaSeDis is available at http://mlodis.phasep.pro.</p>","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12208530/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143560320","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}