Biology subjects

Fay, P. A.

Publications and source records attributed to Fay, P. A..

5 recordsLinked to original sources

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

Correlational selection and genetic architecture promote the leaf economics spectrum in a perennial grass

The leaf economics spectrum (LES) is hypothesized to result from a trade-off between resource acquisition and conservation. Yet few studies have examined the evolutionary mechanisms behind the LES, perhaps because most species exhibit relatively specialized leaf economics strategies. In a genetic mapping population of the phenotypically diverse grass Panicum virgatum, we evaluate two interacting mechanisms that may drive LES evolution: 1) genetic architecture, where multiple traits are coded by the same gene (pleiotropy) or by genes in close physical proximity (linkage), and 2) correlational selection, where selection acts non-additively on combinations of multiple traits. We found evidence suggesting that shared genetic architecture (pleiotropy) controls covariation between two pairs of leaf economics traits. Additionally, at five common gardens spanning 17 degrees of latitude, correlational selection favored particular combinations of leaf economics traits. Together, these results demonstrate how the LES can evolve within species.

ecology↗

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↗

bioRxiv2021

Multiple resource limitations explain biomass-precipitation relationships in grasslands

Interannual variability in grassland primary production is strongly driven by precipitation, nutrient availability and herbivory, but there is no general consensus on the mechanisms linking these variables. If grassland biomass is limited by the single most limiting resource at a given time, then we expect that nutrient addition will not affect biomass production at arid sites. We conducted a distributed experiment manipulating nutrients and herbivores at 44 grassland sites in 8 regions around the world, spanning a broad range in aridity. We estimated the effects of 5-11 years of nutrient addition and herbivore exclusion treatments on precipitation sensitivity of biomass (proportional change in biomass relative to proportional change in rainfall among years), and the biomass in the driest year (to measure treatment effects when water was most limiting) at each site. Grazer exclusion did not interact with nutrients to influence driest year biomass or sensitivity. Nutrient addition increased driest year biomass by 74% and sensitivity by 0.12 (proportional units), and that effect did not change across the range of aridity spanned by our sites. Grazer exclusion did not interact with nutrients to influence sensitivity or driest year biomass. At almost half of our sites, the previous year's rainfall explained as much variation in biomass as current year precipitation. Overall, our distributed fertilization experiment detected co-limitation between nutrients and water governing grasslands, with biomass sensitivity to precipitation being limited by nutrient availability irrespective of site aridity and herbivory. Our findings refute the classical ideas that grassland plant performance is limited by the single most limiting resource at a site. This suggests that nutrient eutrophication will destabilize grassland ecosystems through increased sensitivity to precipitation variation.

ecology↗

bioRxiv2019

Geographic variation in the genetic basis of resistance to leaf rust in locally adapted ecotypes of the biofuel crop switchgrass (Panicum virgatum)

O_LILocal adaptation is an important process in plant evolution, which can be impacted by differential pathogen pressures along environmental gradients. However, the degree to which pathogen resistance loci vary in effect across space and time is incompletely described. C_LIO_LITo understand how the genetic architecture of resistance varies across time and geographic space, we quantified rust (Puccinia spp.) severity in switchgrass (Panicum virgatum) plantings at eight locations across the central United States for three years and conducted quantitative trait locus (QTL) mapping for rust progression. C_LIO_LIWe mapped several variable QTLs, but two large-effect QTLs which we have named Prr1 and Prr2 were consistently associated with rust severity in multiple sites and years, particularly in northern sites. In contrast, there were numerous small-effect QTLs at southern sites, indicating a genotype-by-environment interaction in rust resistance loci. Interestingly, Prr1 and Prr2 had a strong epistatic interaction, which also varied in strength and direction of effect across space. C_LIO_LIOur results suggest that abiotic factors covarying with latitude interact with the genetic loci underlying plant resistance to control rust infection severity. Further, our results indicate that segregating genetic variation in epistatically interacting loci may play a key role in determining response to infection across geographic space. C_LI

genomics↗