Tianyuan Zhang, Mian Jiang, Hanzhou Li, Yunyun Gao, Salsabeel Yousuf, Kaimin Yu, Xinxin Yi, Jun Wang, Lulu Yang, Yong-Xin Liu
{"title":"使用纳米孔和PacBio进行长读元基因组测序的计算工具和资源。","authors":"Tianyuan Zhang, Mian Jiang, Hanzhou Li, Yunyun Gao, Salsabeel Yousuf, Kaimin Yu, Xinxin Yi, Jun Wang, Lulu Yang, Yong-Xin Liu","doi":"10.1093/gpbjnl/qzaf075","DOIUrl":null,"url":null,"abstract":"<p><p>In recent years, the field of shotgun metagenomics has witnessed remarkable advancements, primarily driven by the development and refinement of next-generation sequencing technologies, particularly long-read sequencing platforms such as Nanopore and PacBio. These platforms have significantly improved the ability to analyze microbial communities directly from environmental samples, providing valuable information on their composition, function, and dynamics without the need for pure cultivation. These technologies enhance metagenomic data assembly, annotation, and analysis by addressing longer reads, higher error rates, and complex data. In this review, we provide a comprehensive overview of the historical development of long-read metagenomics, highlighting significant landmarks and advancements. We also explore the diverse applications of long-read metagenomics, emphasizing its impact across various fields. Additionally, we summarize the essential computational resources, including software, databases, and packages, developed to enhance the efficiency and accuracy of metagenomic analysis. Finally, we provide a practical guide for the installation and use of notable software available on GitHub (https://github.com/zhangtianyuan666/LongMetagenome). Overall, this review assists the metagenomics community in exploring microbial life in unprecedented depth by providing a roadmap for successful resource utilization and emphasizing possibilities for innovation.</p>","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":7.9000,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Computational Tools and Resources for Long-read Metagenomic Sequencing Using Nanopore and PacBio.\",\"authors\":\"Tianyuan Zhang, Mian Jiang, Hanzhou Li, Yunyun Gao, Salsabeel Yousuf, Kaimin Yu, Xinxin Yi, Jun Wang, Lulu Yang, Yong-Xin Liu\",\"doi\":\"10.1093/gpbjnl/qzaf075\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>In recent years, the field of shotgun metagenomics has witnessed remarkable advancements, primarily driven by the development and refinement of next-generation sequencing technologies, particularly long-read sequencing platforms such as Nanopore and PacBio. These platforms have significantly improved the ability to analyze microbial communities directly from environmental samples, providing valuable information on their composition, function, and dynamics without the need for pure cultivation. These technologies enhance metagenomic data assembly, annotation, and analysis by addressing longer reads, higher error rates, and complex data. In this review, we provide a comprehensive overview of the historical development of long-read metagenomics, highlighting significant landmarks and advancements. We also explore the diverse applications of long-read metagenomics, emphasizing its impact across various fields. Additionally, we summarize the essential computational resources, including software, databases, and packages, developed to enhance the efficiency and accuracy of metagenomic analysis. Finally, we provide a practical guide for the installation and use of notable software available on GitHub (https://github.com/zhangtianyuan666/LongMetagenome). Overall, this review assists the metagenomics community in exploring microbial life in unprecedented depth by providing a roadmap for successful resource utilization and emphasizing possibilities for innovation.</p>\",\"PeriodicalId\":94020,\"journal\":{\"name\":\"Genomics, proteomics & bioinformatics\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":7.9000,\"publicationDate\":\"2025-08-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Genomics, proteomics & bioinformatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1093/gpbjnl/qzaf075\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Genomics, proteomics & bioinformatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/gpbjnl/qzaf075","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Computational Tools and Resources for Long-read Metagenomic Sequencing Using Nanopore and PacBio.
In recent years, the field of shotgun metagenomics has witnessed remarkable advancements, primarily driven by the development and refinement of next-generation sequencing technologies, particularly long-read sequencing platforms such as Nanopore and PacBio. These platforms have significantly improved the ability to analyze microbial communities directly from environmental samples, providing valuable information on their composition, function, and dynamics without the need for pure cultivation. These technologies enhance metagenomic data assembly, annotation, and analysis by addressing longer reads, higher error rates, and complex data. In this review, we provide a comprehensive overview of the historical development of long-read metagenomics, highlighting significant landmarks and advancements. We also explore the diverse applications of long-read metagenomics, emphasizing its impact across various fields. Additionally, we summarize the essential computational resources, including software, databases, and packages, developed to enhance the efficiency and accuracy of metagenomic analysis. Finally, we provide a practical guide for the installation and use of notable software available on GitHub (https://github.com/zhangtianyuan666/LongMetagenome). Overall, this review assists the metagenomics community in exploring microbial life in unprecedented depth by providing a roadmap for successful resource utilization and emphasizing possibilities for innovation.