Discussion
There is growing appreciation for the important and often complex
interactions that exist between plants and their associated microbial
communities. Exploring the genetic architecture of plant
trait-microbiome interactions is an important step in determining if
these interactions play a role in local adaptation and evolution. Here,
we conducted a QTL study with a P. hallii RIL mapping population
in soils inoculated with microbiomes from native P. halliihabitats to observe the impact of microbiomes on plant traits and
genetic architecture. We found that the microbiota in the natural
habitat of the RIL parents are distinct and served as suitable
experimental treatments to quantify the effects of microbiota on
host-plant traits. In this study, soils inoculated with native
microbiomes drive trait plasticity in both above and below ground
traits, and these effects were both general and location specific with
respect to the origin of the microbial inoculum. We found QTL that
displayed GxE for ten of twelve measured traits, suggesting widespread
genetic variation in trait responses to plant-microbiome interaction. We
also identified epistatically interacting QTL for root diameter present
only in microbiomes from native locations, indicating that hybridization
of ecotypes may disrupt genes and their interaction with microbes
through root characteristics. Overall, our study suggests that the
genetic architecture of host functional traits is significantly impacted
by microbial associations.
It is clear that host traits are impacted by microbial communities.
Although soil microbes interact directly and indirectly with the root
system, they can induce changes that affect the entire plant. The
presence of microbiomes from native soil inocula induced trait
plasticity in above and belowground traits for the parents that was
general and location specific (Fig. 2). For example, traits linked to
resource acquisition such as specific leaf area (SLA) and specific root
length (SRL) were altered in response to the presence of microbiomes.
High SLA correlates with high nitrogen content and low structural
investment in leaves, which yields high rates of photosynthesis to
promote rapid growth (Cornelissen et al. 2003; Reich et al. 1997), a
trait necessary in xeric environments with short seasons terminated by
drought. This is consistent with high SRL, where plants produce longer
and thinner roots with less structural input to search for water
(Balachowski et al. 2016). SLA showed a plastic response to location
specific native microbiomes: SLA was increased for plants with the AI
microbiome and decreased for plants with the CI microbiome. This
observed pattern in SLA is consistent with the directionality of
ecotypic divergence. Moreover, SRL showed GxE in response to microbiomes
that was also concordant with the direction of parental trait
divergence: with xeric adapted hallii showing higher SRL in the
presence of native microbiomes while mesic adapted filipes showed
lower SRL.
We detected two groups of QTL interacting with native microbiomes. The
first responded to native soil inocula regardless of their origin and
the second interacted with native soil inoculum from only one site. For
example, QTL for root number 8@33.1 was present only in the MI treatment
and not detected in native treatments, suggesting that native
microbiomes reduce genetic divergence for this trait (Fig. 4a). This
could be explained by microbial taxa which flourished under MI treatment
given that the niche competition was relaxed. QTL for SRL (4@19.1) and
RMR (3@74.9) showed location specific GxE (Fig. 4b, c); plants with thefilipes allele in the CI treatment resulted in a higher trait
value. This is opposite to the direction of SRL trait divergence in
parental ecotypes and to their response to the CI treatment. Eight QTLs
showed location specific GxE to the AI treatment (Fig. 4d-k). Our
previous study conducted at the panicle emergence stage suggested that
xeric hallii employs a fast-acquisitive strategy for drought
escape by acquiring nutrients rapidly and flowering quickly to enter
dormancy before the onset of summer drought (Khasanova et al. 2019).
This is consistent with current study conducted at the tillering stage
where plants with the hallii allele in interaction with the AI
microbiome produced more root and shoot biomass. This is accomplished by
the increased production of tillers with roots to support them. Root
systems of plants with these hallii QTL hotspots produced longer
and thinner roots, putatively allowing increased foraging and resource
acquisition. Four of these QTL present in interaction with AI clustered
in the genomic “hotspot” on chromosome seven and three QTL clustered
on chromosome nine. This common genetic control of ecotype
differentiating traits involving above and below ground traits suggests
that these factors interact with the AI microbiome in tandem,
potentially contributing to ecotype divergence and local adaptation.
We also identified epistatically interacting QTL for root diameter
present only in treatments with microbiomes from native locations (Fig.
5). When lines are homozygous for either hallii or filipesalleles at both of the interacting QTL, individuals produce smaller
diameter roots. In contrast, individuals with mismatched genotypes
(HH/FF) at the pair of interacting loci develop larger diameter roots.
However, the observed epistatic QTL effects did not translate to
decreases in aboveground biomass. This hybrid mismatched that have
unusual phenotypes could represent either hybrid vigor or breakdown –
but selection studies looking at how these phenotypes impact performance
will be needed to further evaluate links between epistasis-microbiome
interactions and root developmental responses.
A strength of our inoculation approach was prioritizing community
effects, as opposed to the effect of single bacterial inoculants.
However, given the exciting experimental advances of isolated bacterial
strains in synthetic communities, targeted communities using locally
adapted bacterial strains or combinatorics (Paredes 2018) could be used
to address how the presence / absence of particular microbes impact
plant phenotypes. In addition, it is intriguing to speculate on the
genes and molecular mechanisms underlying the host x microbiome QTL
detected in our study. It could be that these QTL harbor genes that
interact only indirectly with the host microbiome, perhaps through
abundance of soil nutrients as modified by microbes. For example,
certain soil microbes in our inoculates may alter the abundance or
availability of soil nutrients with subsequent consequences for genetic
variation in root or shoot growth. It may be that QTL are related to
root exudates or metabolites released that may recruit or amplify key
beneficial microbes with subsequent impacts on available nutrients.
There are many examples of soil resource abundances of key nutrients
impacting plant growth, including genes that demonstrated plastic
responses to nutrient availability (Brumbarova & Ivanov 2019).
Alternatively, it may be that the genes within QTL intervals are
involved in more direct interactions with microbes. For example, recent
studies show that phytohormones, microRNAs and secreted peptides are
known to recruit and foster the establishment of symbiotic arbuscular
mycorrhizal fungi (Müller & Harrison 2019). Moreover, Finkel et
al. 2020 recently discovered an important role of the bacterial
genus Variovorax in attenuating the negative effects on root
growth imposed by other bacterial isolates via modification of auxin
concentration gradients in the rhizosphere. Plants also deploy extensive
immune repertoires to ward off pathogens and control access of microbes
to endophytic compartments (Chen et al. 2020) and some of our
interactions may be related to ecotypic specific resistance or
susceptibility. Our observation of an epistatic interaction is
especially interesting as they may represent sensing and signaling
pathways that are triggered or directed by microbes. In our case,
epistatic interactions may also represent hybrid incompatibilities
between ecotypes that are driven by the microbial community. Given the
broad confidence intervals of our genome wide scans, we resist the
temptation to consider and discuss specific candidate genes.
Nevertheless, we emphasize that our approach leads to a direct pathway
of fine-mapping and the identification and cloning of new genes involved
in plant-microbiome interactions.
Our results show that microbiomes impact the influence of genetic
architecture on plant traits in two ecotypes of Panicum hallii .
These effects were broadly divided into two categories, effects
dependent upon the presence of inoculated microbiomes in general and
effects dependent upon microbiomes originating from a specific location
of origin. This pattern sheds light on the role biotic factors may play
in ecotype divergence and raises questions about how microbes impact the
genetic architecture of plant quantitative traits, potentially leading
to local adaptation and ultimately speciation. Further work in this
system has several pathways forward. Broad characterization of microbial
communities can be used to determine how genetic variation shapes
microbial communities as well as individual microbes. For example, this
approach may allow for differentiating the effects that are mediated by
plant-fungal interactions vs. plant-bacterial interactions. Once more is
known about specific members of the microbial community that play large
roles in impacting plant traits, reductionist approaches including
targeted inoculations of bacterial / fungal strains and reverse genetic
approaches could be used to identify specific mechanisms underlying
plant-microbe interactions.