PDF(Pubmed)
Abstract：
Unraveling bacterial gene function drives progress in various areas, such as food production, pharmacology, and ecology. While omics technologies capture high-dimensional phenotypic data, linking them to genomic data is challenging, leaving 40-60% of bacterial genes undescribed. To address this bottleneck, we introduce Scoary2, an ultra-fast microbial genome-wide association studies (mGWAS) software. With its data exploration app and improved performance, Scoary2 is the first tool to enable the study of large phenotypic datasets using mGWAS. As proof of concept, we explore the metabolome of yogurts, each produced with a different Propionibacterium reichii strain and discover two genes affecting carnitine metabolism.
摘要：
解开细菌基因功能推动了各个领域的进步，比如食品生产，药理学,和生态。虽然组学技术捕获高维表型数据，将它们与基因组数据联系起来是具有挑战性的，留下40-60%的细菌基因没有描述。为了解决这个瓶颈，我们介绍了Scoary2，一种超快速的微生物全基因组关联研究（mGWAS）软件。凭借其数据探索应用程序和改进的性能，Scoary2是第一个使用mGWAS研究大型表型数据集的工具。作为概念的证明，我们探索酸奶的代谢组，每一个生产不同的物理丙酸杆菌菌株，并发现两个基因影响肉碱代谢。
