Data from: Genome-wide association studies across environmental and genetic contexts reveal complex genetic architecture of symbiotic extended phenotypes

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 symbiotic extended phenotypes, 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 – partner quality, 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, 1)
loci whose identities depend on the environment, 2) those that depend on
the host genotype with which rhizobia interact, and 3) universal loci that
are likely important in all or most environments. IMPORTANCE: 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.