INTRODUCTION
Silphium integrifolium Michx (commonly known as rosinweed or silflower) is a native perennial prairie species being domesticated for production as a forage and oilseed species (Vilela et al., 2018; Van Tassel et al., 2017). The plant’s perennial nature allows it to provide novel ecosystem services in agronomic production systems (Glover et al., 2010; Van Tassel et al., 2017) while producing oilseeds with similar nutritional composition to annual sunflower (Helianthus annuus L. (Asterales: Asteraceae) seeds (Reinert et al., 2018). However, S. integrifolium suffers infections from diverse pathogen enemies across its native range. The stems, leaves, and flowers can be infected with multiple strains (Turner, unpublished observations) of Puccinia silphii Schwein (1832), or Silphium rust (Turner et al., 2018),Colletotrichum silphii Davis (1919) (Horst 2008) syn. andColletotrichum dematium (Pers.) Grove (Cybernome; Farr 1989) called leaf blotch hereafter. Recently, Silphium clear vein (SCV) leaf and stem disease has been described and hypothesized to be caused by a virus based on the identification of viral sequences inSilphium integrifolium that are similar to the Dahlia common Mosaic Virus (DCMV) and Dahlia endogenous plant pararetroviral sequence (DvEPRS, formerly DMV-D10) (Almeyda, 2014; Cassetta et al., 2023). Understanding how S. integrifolium defends against these pathogens is crucial for progress in breeding programs and will elucidate evolutionary questions posed in the species (Cassetta et al., 2023, Van Tassel et al, 2017). In this study, plants from 12 wild populations of S. integrifolium were planted in a reciprocal transplant design to better understand adaptation to disease pressures along a rainfall gradient. Phenotypic data revealed that these wild populations have distinctive morphologies and showed variable levels of tolerance to biotic stresses, such as pests and pathogens (Peterson et al., in prep). Individuals with resistance to diseases of S. integrifolium were visually identified in the study, and have been previously identified in breeding populations (Turner et al., 2018), but the genetic basis of disease resistance has not been investigated. Here, we look at the diversity of disease resistance genes in wild populations of S. integrifolium to answer evolutionary questions regarding adaptation of wild populations to their pathogen pressures and suggest applications for germplasm enhancement.
Environments with high precipitation are conducive to increased pathogen pressures (Clarkson et al., 2014; Granke and Hausbeck 2010; Islam and Toyota, 2004; Magarey et al., 2005; Rowlandson et al., 2015). Several studies have found patterns of resistance alleles consistent with pathogen selection intensity increasing with precipitation (Wahl 1970, Abbott, Brown, and Burdon 1991, Dong et al. 2009). We hypothesize thatS. integrifolium populations evolved in areas with high precipitation will have a more diverse complement of disease resistance genes to deal with this challenge. To test this hypothesis, we collected seeds from S. integrifolium stands from four prairie remnants each in three geographic regions in the Central Plains of the United States. The regions are situated along a gradient of effective precipitation, or the amount of rainfall that is not lost to potential evapotranspiration, referred to in this study as the climate moisture index (CMI). We refer to these regions as “West”, from West-Central Kansas, “Central”, from Eastern Kansas, and “East”, from Central Illinois (Figure 1). Prairie remnants in the West receive around -55 kg/m2/month of CMI per year, whereas sites in the East receive closer to -15 kg/m2/month (Table 1). We note that plant defensive gene diversity increased along this gradient inAndropogon gerardii , a native perennial grass that co-occurs withS. integrifolium (Rouse et al. 2011) and soil pathogen diversity also increased along this same gradient (Delavaux et al. 2021).
A major class of disease resistance genes in plants are the cytoplasmic nucleotide binding and leucine-rich repeat (NLR) genes. (Caplan et al., 2008; Eitas and Dangl, 2010). These NLRs, (hereafter, R genes), often contain an N-terminal domain that is either of a coiled-coil type, called CNLs, or a toll-interleukin-like type (TNLs), whose divergence predates the split between monocots and eudicots (Meyers et al., 1999), estimated to be about 160 Mya by TimeTree (Kumar et al., 2017). R genes are highly diverse, numbering in the hundreds in many plant species (Jupe et al., 2012; Toda et al., 2020). These genes evolve rapidly and are enriched in presence/absence variation even at the intraspecies level, limiting the utility of a single reference genome to elucidate the diversity of R genes within a species. This study employed R-gene enrichment sequencing (RenSeq; Jupe et al, 2013), which uses DNA baits to reduce complexity of genomic DNA libraries. The baits we designed come from the common sunflower, Helianthus annuus L., which is separated from S. integrifolium by between 22 (Meireles et al., 2020) and 33 million years ago (Zhang et al., 2021) . We sequenced the RenSeq libraries from S. integrifolium plants across the rainfall gradient using both Illumina short-read and PacBio long-read technologies.
RenSeq is not a new technology – having been developed in 2013. It has been used to address basic problems in plant immunity (Jupe et al., 2013) and applied questions in plant breeding in numerous crop species and their wild relatives for crop improvement (e.g. Arora et al., 2019) and to understand mechanisms of plant immunity (e.g. Witek et al., 2021). Despite the utility of RenSeq in plant breeding projects, and in helping us better understand plant disease resistance, this technology has not been used to address basic evolutionary and biogeographical questions.
Using both simple linear models as well as mixed effect models, we found a significant positive correlation between the effective precipitation of a plant’s host prairie and the number of R genes detected in both the Illumina and PacBio datasets. While this observation does not itself prove the broader theory that disease resistance correlates with rainfall in plants, it is certainly consistent with theoretical expectations, and should motivate additional evaluation of these ideas in other taxa. Because we demonstrate the economic utility of the RenSeq approach in non-model systems, our work not only points to data consistent with our hypothesis but paves the way towards evaluating the generality of this finding.