Marjan Barazandeh, Hamid Kian Gaikani, Rutuja Pattanshetti, Joseph Uche Ogbede, Sunita Sinha, Rachel Moore, Christopher E Carr, Guri Giaever, Corey Nislow
{"title":"Bar-seq: A robust, platform-agnostic method for massively parallel cell-based screens.","authors":"Marjan Barazandeh, Hamid Kian Gaikani, Rutuja Pattanshetti, Joseph Uche Ogbede, Sunita Sinha, Rachel Moore, Christopher E Carr, Guri Giaever, Corey Nislow","doi":"10.1093/g3journal/jkaf166","DOIUrl":null,"url":null,"abstract":"<p><p>Bar-seq (barcode sequencing) is a high-throughput method originally developed for systematically identifying gene-drug interactions and genetic dependencies in yeast using pooled deletion mutant libraries. This approach enables high-resolution profiling of large mutant libraries over time, across diverse experimental conditions, providing relative fitness values for each individual within the population. As the technology for enumerating barcodes has evolved, we have continued to incorporate improvements to the method. Here, we present an optimized Bar-seq workflow adaptable to multiple sequencing platforms, including instruments from Illumina, MGI, Element, and Oxford Nanopore. We highlight the advantages and limitations of each approach to aid in experimental design decisions. We introduce refinements in barcode amplification, sequencing strategies, and data analysis to enhance accuracy and scalability while making adoption as straightforward as possible.</p>","PeriodicalId":12468,"journal":{"name":"G3: Genes|Genomes|Genetics","volume":" ","pages":""},"PeriodicalIF":2.2000,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"G3: Genes|Genomes|Genetics","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1093/g3journal/jkaf166","RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}
引用次数: 0
Abstract
Bar-seq (barcode sequencing) is a high-throughput method originally developed for systematically identifying gene-drug interactions and genetic dependencies in yeast using pooled deletion mutant libraries. This approach enables high-resolution profiling of large mutant libraries over time, across diverse experimental conditions, providing relative fitness values for each individual within the population. As the technology for enumerating barcodes has evolved, we have continued to incorporate improvements to the method. Here, we present an optimized Bar-seq workflow adaptable to multiple sequencing platforms, including instruments from Illumina, MGI, Element, and Oxford Nanopore. We highlight the advantages and limitations of each approach to aid in experimental design decisions. We introduce refinements in barcode amplification, sequencing strategies, and data analysis to enhance accuracy and scalability while making adoption as straightforward as possible.
期刊介绍:
G3: Genes, Genomes, Genetics provides a forum for the publication of high‐quality foundational research, particularly research that generates useful genetic and genomic information such as genome maps, single gene studies, genome‐wide association and QTL studies, as well as genome reports, mutant screens, and advances in methods and technology. The Editorial Board of G3 believes that rapid dissemination of these data is the necessary foundation for analysis that leads to mechanistic insights.
G3, published by the Genetics Society of America, meets the critical and growing need of the genetics community for rapid review and publication of important results in all areas of genetics. G3 offers the opportunity to publish the puzzling finding or to present unpublished results that may not have been submitted for review and publication due to a perceived lack of a potential high-impact finding. G3 has earned the DOAJ Seal, which is a mark of certification for open access journals, awarded by DOAJ to journals that achieve a high level of openness, adhere to Best Practice and high publishing standards.