Department of Plant and Microbial Biology, University of California, Berkeley, CA, USA.
Plant Gene Expression Center, USDA-ARS, Albany, CA, USA.
Methods Mol Biol. 2022;2481:353-367. doi: 10.1007/978-1-0716-2237-7_20.
Plants form intimate associations with microorganisms, and these associations are directly impacted by the host genotype. However, identifying specific host genetic pathways that influence these microbial interactions has proved challenging. Genome-wide association-based approaches that use features of microbiome composition as a quantitative trait represent a novel and underutilized strategy to identify such pathways. Several recent studies have demonstrated the potential utility of plant microbiome-based genome-wide association studies (GWAS). In this chapter, we describe the process of implementing GWAS using the plant microbiome as the primary quantitative trait, considering experimental design, sample harvest, and processing, but with an emphasis on data filtering, data normalization, and statistical analyses.
植物与微生物形成密切的联系，而这些联系直接受到宿主基因型的影响。然而，确定影响这些微生物相互作用的特定宿主遗传途径一直具有挑战性。基于全基因组关联的方法，使用微生物组组成的特征作为数量性状，代表了一种识别这些途径的新颖且未充分利用的策略。最近的几项研究表明，基于植物微生物组的全基因组关联研究（GWAS）具有潜在的应用价值。在本章中，我们描述了使用植物微生物组作为主要数量性状来实施 GWAS 的过程，包括实验设计、样本采集和处理，但重点是数据过滤、数据归一化和统计分析。
