Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaigngrid.35403.31, Urbana, Illinois, USA.
Department of Plant Biology, University of Illinois at Urbana-Champaigngrid.35403.31, Urbana, Illinois, USA.
mBio. 2022 Dec 20;13(6):e0182322. doi: 10.1128/mbio.01823-22. Epub 2022 Oct 26.
A goal of modern biology is to develop the genotype-phenotype (G→P) map, a predictive understanding of how genomic information generates trait variation that forms the basis of both natural and managed communities. As microbiome research advances, however, it has become clear that many of these traits are , being governed by genetic variation encoded not only by the host's own genome, but also by the genomes of myriad cryptic symbionts. Building a reliable G→P map therefore requires accounting for the multitude of interacting genes and even genomes involved in symbiosis. Here, we use naturally occurring genetic variation in 191 strains of the model microbial symbiont Sinorhizobium meliloti paired with two genotypes of the host Medicago truncatula in four genome-wide association studies (GWAS) to determine the genomic architecture of a key symbiotic extended phenotype-, or the fitness benefit conferred to a host by a particular symbiont genotype, within and across environmental contexts and host genotypes. We define three novel categories of loci in rhizobium genomes that must be accounted for if we want to build a reliable G→P map of partner quality; namely, (i) loci whose identities depend on the environment, (ii) those that depend on the host genotype with which rhizobia interact, and (iii) universal loci that are likely important in all or most environments. Given the rapid rise of research on how microbiomes can be harnessed to improve host health, understanding the contribution of microbial genetic variation to host phenotypic variation is pressing, and will better enable us to predict the evolution of (and select more precisely for) symbiotic extended phenotypes that impact host health. We uncover extensive context-dependency in both the identity and functions of symbiont loci that control host growth, which makes predicting the genes and pathways important for determining symbiotic outcomes under different conditions more challenging. Despite this context-dependency, we also resolve a core set of universal loci that are likely important in all or most environments, and thus, serve as excellent targets both for genetic engineering and future coevolutionary studies of symbiosis.
现代生物学的目标之一是构建基因型-表型（G→P）图谱，以预测基因组信息如何产生导致自然和管理群落形成的性状变异。然而，随着微生物组研究的进展，很明显，许多这些性状受到遗传变异的控制，这些遗传变异不仅由宿主自身的基因组编码，还由无数隐藏共生体的基因组编码。因此，构建可靠的 G→P 图谱需要考虑到共生体中涉及的众多相互作用的基因甚至基因组。在这里，我们使用模型微生物共生体 Sinorhizobium meliloti 的 191 个菌株中的自然发生的遗传变异，以及两个宿主 Medicago truncatula 的基因型，在四个全基因组关联研究（GWAS）中，确定关键共生扩展表型的基因组结构，或特定共生体基因型赋予宿主的适应性优势，在不同环境和宿主基因型中。我们定义了 Rhizobium 基因组中必须考虑的三个新的类别，以便我们构建可靠的伙伴质量 G→P 图谱；即（i）其身份取决于环境的位点，（ii）依赖于与 Rhizobia 相互作用的宿主基因型的位点，以及（iii）可能在所有或大多数环境中都很重要的通用位点。鉴于研究微生物组如何被利用来改善宿主健康的研究迅速兴起，了解微生物遗传变异对宿主表型变异的贡献迫在眉睫，这将使我们能够更好地预测对宿主健康产生影响的共生扩展表型的进化，并更精确地选择这些表型。我们发现控制宿主生长的共生体位点的身份和功能都具有广泛的上下文依赖性，这使得预测在不同条件下确定共生结果的基因和途径更加具有挑战性。尽管存在这种上下文依赖性，但我们也确定了一组核心的通用位点，这些位点可能在所有或大多数环境中都很重要，因此，它们是遗传工程和未来共生进化研究的极好目标。
