Rouquette, F. M. | Search bioRxiv

bioRxiv2024

Local adaptation of both plant and pathogen: an arms-race compromise in switchgrass rust

O_LIIn widespread species, parasites can locally adapt to host populations, or hosts can locally adapt to resist parasites. Parasites with rapid life cycles locally adapt more quickly, but host diversity, selective pressure, and climatic factors impact coevolution. C_LIO_LITo better understand local adaptation in co-evolved host-parasite systems, we examined switchgrass (Panicum virgatum), and its leaf rust pathogen (Puccinia novopanici) across a latitudinal range in North America. We grew diverse switchgrass genotypes in ten replicated common gardens spanning 16.78{degrees} latitude for three years, measuring rust severity from natural infection. We conducted genome wide association mapping to identify genetic loci associated with rust severity. C_LIO_LIGenetically differentiated rust populations were locally adapted to northern and southern switchgrass, despite host local adaptation in the same regions. Rust resistance was highly polygenic, and distinct loci were associated with rust severity in the north and south. We narrowed a previously identified large-effect QTL for rust severity to a candidate YSL3-like gene, and linked numerous other loci to immunity-related genes. C_LIO_LIBoth hosts and parasites can be locally adapted when parasites have a lower impact on fitness than other local selection pressures. In switchgrass, our results suggest variation in fungal resistance mechanisms between locally adapted regions. C_LI

evolutionary biology↗

bioRxiv2021

Mapping of genotype-by-environment interactions in phenology identifies two cues for flowering in switchgrass (Panicum virgatum)

The timing of vegetative and reproductive growth in plants ("phenological timings") depend on genetic effects (G), environmental (e.g., weather) cues, and their interaction. Here, we measure phenological timings in two highly divergent switchgrass (Panicum virgatum) subpopulations using repeated plantings of cloned individuals at eight sites across the central United States. The timing of vegetative growth for the two subpopulations reversed between their two natural ranges and had strong negative correlations between these regions; in contrast, the timing of flowering was positively correlated between gardens. We expect that these phenotypic correlations consist of polygenic effects on phenology which have distinct patterns of GxE segregating at different mapped loci. Thus, we infer the mixture of ways genetic effects impact phenological timings, such as across common gardens (GxE) or with weather cues (GxWeather). We demonstrate that we can identify genetic variation with GxWeather and assign genetic loci to specific weather-based cues or other patterns. For example, in the Gulf subpopulation, 65% of genetic effects on the timing of vegetative growth covary with daylength 14 days prior to green-up date, and 33% of genetic effects on the timing of flowering covary with cumulative rainfall in the week prior to flowering. However, most variation in genetic effects cannot be attributed to variation in weather variables. Selective breeding for particular alleles at GxWeather loci could alter flowering responsiveness in a photoperiod or rainfall-specific way. More broadly, our approach refines the characterization of genotype-by-environment interactions and can be implemented in any species phenotyped in multiple environments.

genetics↗