Barazandeh Marjan, Gaikani Hamid Kian, Pattanshetti Rutuja, Ogbede Joseph Uche, Sinha Sunita, Moore Rachel, Carr Christopher E, Giaever Guri, Nislow Corey
Pharmaceutical Sciences, The University of British Columbia, 2405 Wesbrook Mall, Vancouver, BC, Canada V6T 1Z3.
UBC Sequencing and Bioinformatics Consortium, Pharmaceutical Sciences, The University of British Columbia, 2405 Wesbrook Mall, Vancouver, BC, Canada V6T 1Z3.
G3 (Bethesda). 2025 Sep 3;15(9). doi: 10.1093/g3journal/jkaf166.
Barcode sequencing (Bar-seq) 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.
条形码测序（Bar-seq）是一种高通量方法，最初是为了利用汇集的缺失突变体文库系统地鉴定酵母中的基因-药物相互作用和遗传依赖性而开发的。这种方法能够随着时间的推移，在不同的实验条件下对大型突变体文库进行高分辨率分析，为群体中的每个个体提供相对适合度值。随着条形码计数技术的发展，我们不断对该方法进行改进。在这里，我们展示了一种优化的Bar-seq工作流程，它适用于多种测序平台，包括Illumina、MGI、Element和Oxford Nanopore的仪器。我们强调了每种方法的优缺点，以帮助做出实验设计决策。我们介绍了条形码扩增、测序策略和数据分析方面的改进，以提高准确性和可扩展性，同时使采用过程尽可能简单直接。
