Two shifts in evolutionary lability underlie independent gains and losses of root-nodule symbiosis in a single clade of plants

Abstract

Root nodule symbiosis (RNS) allows plants to access atmospheric nitrogen converted into usable forms through a mutualistic relationship with soil bacteria. RNS is a complex trait requiring coordination from both the plant host and the bacterial symbiont, and pinpointing the evolutionary origins of root nodules is critical for understanding the genetic basis of RNS. This endeavor is complicated by data limitations and the intermittent presence of RNS in a single clade of ca. 30,000 species of flowering plants, i.e., the nitrogen-fixing clade (NFC). We developed the most extensive de novo phylogeny for all major lineages of the NFC and an enhanced root nodule trait database to reconstruct the evolution of RNS. Through identification of the evolutionary pathway to RNS gain, we show that shifts among heterogeneous evolutionary rates can explain how a complex trait such as RNS can arise many times across a large phylogeny. Our analysis identifies a two-step process in which an ancestral precursor state gave rise to a more labile state from which RNS was quickly gained at specific points in the NFC. Our rigorous reconstruction of ancestral states illustrates how a two-step pathway could have led to multiple independent gains and losses of RNS, contrary to recent hypotheses invoking just a single gain and numerous losses. RNS may be an example of multi-level convergent evolution, thus requiring a broader phylogenetic and genetic scope for genome-phenome mapping to elucidate mechanisms enabling fully functional RNS.

Testing the evolutionary drivers of nitrogen-fixing symbioses in challenging soil environments

“…The matrix was treated as a single partition, and the character evolution model was chosen with the --parse function in RAxML-NG. We imposed a constraint backbone containing fully resolved clades based on the tree of (Kates et al 2022), so that the backbone was inferred by phylogenomic data, and GenBank data were used primarily for extending taxon sampling. The tree search was implemented for individual orders or clades (i.e., Fabales were split into five clades and Rosales were split into two, given their richness) and stitched to a backbone inferred from 100 representative taxa.…”

“…We manually reviewed and excluded taxa with excessively long branches and tips that violated family monophyly (subfamilial monophyly in larger families), using higher-level taxonomies in the World Checklist of Vascular Plants (WCVP; https://wcvp.science.kew.org/) and family-specific resources for Fabales (Lewis 2005, LPWG 2017 duplicates after synonymization were resolved by expected phylogenetic position based on previous studies or randomly in the case of ties. The final tree product has 54.6% species-level taxon coverage (16,375 species out of ~30,000; Kates et al, 2022). Compared with previous phylogenetic investigations of the nitrogen-fixing clade, e.g., seven loci with 13.0% species-level coverage (Zanne et al 2014;Werner et al 2014;Menge and Crews 2016) and three loci with 3.1% coverage (Li et al 2015), this is the most comprehensive phylogeny to date in terms of species richness and a 28% increase (3,607 species) in sampling compared to (Kates et al 2022), which sampled a partly overlapping set of 12,768 species for 86 loci.…”

“…Root nodule symbiosis (RNS), the encapsulation of endophytic nitrogen-fixing bacteria in specialized plant lateral root structures, is one of the most impactful forms of plant-microbe symbiosis in terrestrial landscapes, as measured by the scale of geographic terrain covered by nodulators (Tamme et al 2021) and the physiological effectiveness of the process itself (Pankievicz et al 2019). Intense research interest has focused on the phylogenetic origin (Soltis et al 1995; Doyle 2011; Werner et al 2014; Li et al 2015; Kates et al 2022) and functional genomic basis (Griesmann et al 2018; van Velzen et al 2018) of RNS itself, as well as understanding factors shaping current diversity and distributions (Sprent et al 2017; Ardley and Sprent 2021). While the origin of RNS has recently attracted renewed interest (reviews: Sprent 2007; Doyle 2011; van Velzen et al 2019), a link between the origins and modern prevalence of RNS remains poorly understood, leaving uncertain the ecological context that may have driven the gain of nodules, as well as how—or if—this gain enabled the ecological dominance of nodulators, and legumes in particular, in harsh landscapes.…”

“…All nodulators are restricted to the nitrogen-fixing clade (NFC), a group of four recognized taxonomic orders (Cucurbitales, Fabales, Fagales, and Rosales) including the legumes and nine other families (Soltis et al 1995; The Angiosperm Phylogeny Group 2016). While species-level data are limited, based on our current understanding of the distribution of nodules (Afkhami et al 2018; Tedersoo et al 2018; Kates et al 2022), approximately 52% of the species in the nitrogen-fixing clade are thought to have the ability to engage in RNS (Kates et al 2022). The nodule organ is structurally diverse; nodulators have been classified based on their bacterial partners, either “rhizobia” (a broad term for bacterial partners of phyla Alphaproteobacteria and Betaproteobacteria, including the traditionally recognized genus Rhizobium , in which case the plant hosts are termed “rhizobial”) or Frankia (phylum Actinobacteria, with the plant hosts termed “actinorhizal”), a division that mostly follows host clade membership and morphological structure of the nodule itself (Pawlowski and Sprent 2008; Ardley and Sprent 2021).…”

“…Despite the popularity of “key innovation” arguments (Hunter 1998; Donoghue 2005; Li et al 2013; Werner et al 2014; Koenen et al 2013), investigations of the nodule itself as a driver of diversification have rarely been attempted (Afkhami et al 2018). This paucity of work relates partly to the challenge of gathering information about an underground trait across large numbers of species and a wide geographical distribution (reviewed in Sprent 2009), a challenge at least partially addressed by several databasing efforts (Werner et al 2014; Afkhami et al 2018; Tedersoo et al 2018; Tamme et al 2021; Kates et al 2022).…”