Wheat dwarfing reshapes plant and fungal development in arbuscular mycorrhizal symbiosis.

The introduction of Reduced height (Rht) dwarfing genes into elite wheat varieties has contributed to enhanced yield gain in high input agrosystems by preventing lodging. Yet, how modern selection for dwarfing has affected symbiosis remains poorly documented. In this study, we evaluated the response of both the plant and the arbuscular mycorrhizal fungus to plant genetic variation at a major Quantitative Trait Locus called QTL 4B2, known to harbor a Rht dwarfing gene, when forming the symbiosis. We used twelve inbred genotypes derived from a diversity base broadened durum wheat Evolutionary Pre-breeding Population and genotyped with a high-throughput Single Nucleotide Polymorphism (SNP) genotyping array. In a microcosm setup segregating roots and the extra-radical mycelium, each wheat genotype was grown with or without the presence of Rhizophagus irregularis. To characterize arbuscular mycorrhizal symbiosis, we assessed hyphal density, root colonization, spore production, and plant biomass. Additionally, we split the variation of these variables due either to genotypes or to the Rht dwarfing genes alone. The fungus exhibited greater development in the roots of Dwarf plants compared to non-Dwarf plants, showing increases of 27%, 37% and 51% in root colonization, arbuscules, and vesicles, respectively. In addition, the biomass of the extra-radical fungal structures increased by around 31% in Dwarf plants. The biomass of plant roots decreased by about 43% in mycorrhizal Dwarf plants. Interestingly, extraradical hyphal production was found to be partly genetically determined with no significant effect of Rht, as for plant biomasses. In contrast, variations in root colonization, arbuscules and extraradical spore production were explained by Rht dwarfing genes. Finally, when mycorrhizal, Dwarf plants had significantly lower total P content, pointing towards a less beneficial symbiosis for the plant and increased profit for the fungus. These results highlight the effect of Rht dwarfing genes on both root and fungal development. This calls for further research into the molecular mechanisms governing these effects, as well as changes in plant physiology, and their implications for fostering arbuscular mycorrhizal symbiosis in sustainable agrosystems.

Correction: The genetic identity of neighboring plants in intraspecific mixtures modulates disease susceptibility of both wheat and rice.

[This corrects the article DOI: 10.1371/journal.pbio.3002287.].

Plant trait relationships are maintained within a major crop species: lack of artificial selection signal and potential for improved agronomic performance.

The exploration of phenotypic spaces of large sets of plant species has considerably increased our understanding of diversification processes in the plant kingdom. Nevertheless, such advances have predominantly relied on interspecific comparisons that hold several limitations. Here, we grew in the field a unique set of 179 inbred lines of durum wheat, Triticum turgidum spp. durum, characterized by variable degrees of artificial selection. We measured aboveground and belowground traits as well as agronomic traits to explore the functional and agronomic trait spaces and to investigate trait-to-agronomic performance relationships. We showed that the wheat functional trait space shared commonalities with global cross-species spaces previously described, with two main axes of variation: a root foraging axis and a slow-fast trade-off axis. Moreover, we detected a clear signature of artificial selection on the variation of agronomic traits, unlike functional traits. Interestingly, we identified alternative phenotypic combinations that can optimize crop performance. Our work brings insightful knowledge about the structure of phenotypic spaces of domesticated plants and the maintenance of phenotypic trade-offs in response to artificial selection, with implications for trade-off-free and multi-criteria selection in plant breeding.

The ecologically relevant genetics of plant-plant interactions.

Interactions among plants have been long recognized as a major force driving plant community dynamics and crop yield. Surprisingly, our knowledge of the ecological genetics associated with variation of plant-plant interactions remains limited. In this opinion article by scientists from complementary disciplines, the international PLANTCOM network identified four timely questions to foster a better understanding of the mechanisms mediating plant assemblages. We propose that by identifying the key relationships among phenotypic traits involved in plant-plant interactions and the underlying adaptive genetic and molecular pathways, while considering environmental fluctuations at diverse spatial and time scales, we can improve predictions of genotype-by-genotype-by-environment interactions and modeling of productive and stable plant assemblages in wild habitats and crop fields.

A genome-wide analysis suggests pleiotropic effects of Green Revolution genes on shade avoidance in wheat.

A classic example of phenotypic plasticity in plants is the suit of phenotypic responses induced by a change in the ratio of red to far-red light (R∶FR) as a result of shading, also known as the shade avoidance syndrome (SAS). While the adaptive consequences of this syndrome have been extensively discussed in natural ecosystems, how SAS varies within crop populations and how SAS evolved during crop domestication and breeding remain poorly known. In this study, we grew a panel of 180 durum wheat (Triticum turgidum ssp. durum) genotypes spanning diversity from wild, early domesticated, and elite genetic compartments under two light treatments: low R:FR light (shaded treatment) and high R:FR light (unshaded treatment). We first quantified the genetic variability of SAS, here measured as a change in plant height at the seedling stage. We then dissected the genetic basis of this variation through genome-wide association mapping. Genotypes grown in shaded conditions were taller than those grown under unshaded conditions. Interaction between light quality and genotype did not affect plant height. We found six QTLs affecting plant height. Three significantly interacted with light quality among which the well-known Rht1 gene introgressed in elite germplasm during the Green Revolution. Interestingly at three loci, short genotypes systematically expressed reduced SAS, suggesting a positive genetic correlation between plant height and plant height plasticity. Overall, our study sheds light on the evolutionary history of crops and illustrates the relevance of genetic approaches to tackle agricultural challenges.

Shift in beneficial interactions during crop evolution.

Plant domestication can be viewed as a form of co-evolved interspecific mutualism between humans and crops for the benefit of the two partners. Here, we ask how this plant-human mutualism has, in turn, impacted beneficial interactions within crop species, between crop species, and between crops and their associated microbial partners. We focus on beneficial interactions resulting from three main mechanisms that can be promoted by manipulating genetic diversity in agrosystems: niche partitioning, facilitation, and kin selection. We show that a combination of factors has impacted either directly or indirectly plant-plant interactions during domestication and breeding, with a trend toward reduced benefits arising from niche partitioning and facilitation. Such factors include marked decrease of molecular and functional diversity of crops and other organisms present in the agroecosystem, mass selection, and increased use of chemical inputs. For example, the latter has likely contributed to the relaxation of selection pressures on nutrient-mobilizing traits such as those associated to root exudation and plant nutrient exchanges via microbial partners. In contrast, we show that beneficial interactions arising from kin selection have likely been promoted since the advent of modern breeding. We highlight several issues that need further investigation such as whether crop phenotypic plasticity has evolved and could trigger beneficial interactions in crops, and whether human-mediated selection has impacted cooperation via kin recognition. Finally, we discuss how plant breeding and agricultural practices can help promoting beneficial interactions within and between species in the context of agroecology where the mobilization of diversity and complexity of crop interactions is viewed as a keystone of agroecosystem sustainability.

From cultivar mixtures to allelic mixtures: opposite effects of allelic richness between genotypes and genotype richness in wheat.

Agroecosystem diversification through increased crop genetic diversity could provide multiple services such as improved disease control or increased productivity. However, we still poorly understand how genetic diversity affects agronomic performance. We grew 179 inbred lines of durum wheat in pure stands and in 202 binary mixtures in field conditions. We then tested the effect of allelic richness between genotypes and genotype richness on grain yield and Septoria tritici blotch disease. Allelic richness was tested at 19K single nucleotide polymorphisms distributed along the durum wheat genome. Both genotype richness and allelic richness could be equal to 1 or 2. Mixtures were overall more productive and less diseased than their pure stand components. Yet, we identified one locus at which allelic richness between genotypes was associated with increased disease severity and decreased grain yield. The effect of allelic richness at this locus was stronger than the effect of genotype richness on grain yield (-7.6% vs +5.7%). Our results suggest that positive effects of crop diversity can be reversed by unfavourable allelic associations. This highlights the need to integrate genomic data into crop diversification strategies. More generally, investigating plant-plant interactions at the genomic level is promising to better understand biodiversity-ecosystem functioning relationships.

Nitrogen availability and plant-plant interactions drive leaf silicon concentration in wheat genotypes.

Estimating plasticity of leaf silicon (Si) in response to abiotic and biotic factors underpins our comprehension of plant defences and stress resistance in natural and agroecosystems. However, how nitrogen (N) addition and intraspecific plant-plant interactions affect Si concentration remains unclear.We grew 19 durum wheat genotypes (Triticum turgidum ssp. durum) in pots, either alone or in intra- or intergenotypic cultures of two individuals, and with or without N. Above-ground biomass, plant height and leaf [Si] were quantified at the beginning of the flowering stage.Nitrogen addition decreased leaf [Si] for most genotypes, proportionally to the biomass increase. Si plasticity to plant-plant interactions varied significantly among genotypes, with both increases and decreases in leaf [Si] when mixed with a neighbour, regardless of the mixture type (intra-/intergenotype). Besides, increased leaf [Si] in response to plant-plant interactions was associated with increased plant height.Our results suggest the occurrence of both facilitation and competition for Si uptake from the rhizosphere in wheat mixtures. Future research should identify which leaf and root traits characterise facilitating neighbours for Si acquisition. We also show that Si could be involved in height gain in response to intraspecific competition, possibly for increasing light capture. This important finding opens up new research directions on Si and plant-plant interactions in both natural ecosystems and agroecosystems. More generally, our results stress the need to explore leaf Si plasticity in responses to both abiotic and biotic factors to understand plant stress resistance. Read the free Plain Language Summary for this article on the Journal blog.

Farming plant cooperation in crops.

Selection of the fittest can promote individual competitiveness but often results in the erosion of group performance. Recently, several authors revisited this idea in crop production and proposed new practices based on selection for cooperative phenotypes, i.e. phenotypes that increase crop yield through decreased competitiveness. These recommendations, however, remain difficult to evaluate without a formal description of crop evolutionary dynamics under different selection strategies. Here, we develop a theoretical framework to investigate the evolution of cooperation-related traits in crops, using plant height as a case study. Our model is tailored to realistic agricultural practices and shows that combining high plant density, high relatedness and selection among groups favours the evolution of shorter plants that maximize grain yield. Our model allows us to revisit past and current breeding practices in light of kin selection theory, and yields practical recommendations to increase cooperation among crops and promote sustainable agriculture.

Preferential helping to relatives: A potential mechanism responsible for lower yield of crop variety mixtures?

Variety mixtures, the cultivation of different genotypes within a field, have been proposed as a way to increase within-crop diversity, allowing the development of more sustainable agricultural systems with reduced environmental costs. Although mixtures have often been shown to over-yield the average of component varieties in pure stands, decreased yields in mixtures have also been documented. Kin selection may explain such pattern, whenever plants direct helping behaviors preferentially toward relatives and thus experience stronger competition when grown with less related neighbors, lowering seed production of mixtures. Using varieties of durum wheat originating from traditional Moroccan agrosystems, we designed a greenhouse experiment to address whether plants reduced competition for light by limiting stem elongation when growing with kin and whether such phenotypic response resulted in higher yield of kin groups. Seeds were sown in groups of siblings and nonkin, each group containing a focal plant surrounded by four neighbors. At the group level, mean plant height and yield did not depend upon relatedness among competing plants. At the individual level, plant height was not affected by genetic relatedness to neighbors, after accounting for direct genetic effects that might induce among-genotype differences in the ability to capture resources that do not depend on relatedness. Moreover, in contrast to our predictions, shorter plants had lower inclusive fitness. Phenotypic plasticity in height was very limited in response to neighbor genotypes. This suggests that human selection in crops may have attenuated shade-avoidance responses to competition for light. Future research on preferential helping to relatives in crops might thus target social traits that drive competition for other resources than light. Overall, our study illustrates the relevance of tackling agricultural issues from an evolutionary standpoint and calls for extending such approaches to a larger set of crop species.

Adaptive plasticity and niche expansion in an invasive thistle.

Phenotypic differentiation in size and fecundity between native and invasive populations of a species has been suggested as a causal driver of invasion in plants. Local adaptation to novel environmental conditions through a micro-evolutionary response to natural selection may lead to phenotypic differentiation and fitness advantages in the invaded range. Local adaptation may occur along a stress tolerance trade-off, favoring individuals that, in benign conditions, shift resource allocation from stress tolerance to increased vigor and fecundity and, therefore, invasiveness. Alternately, the typically disturbed invaded range may select for a plastic, generalist strategy, making phenotypic plasticity the main driver of invasion success. To distinguish between these hypotheses, we performed a field common garden and tested for genetically based phenotypic differentiation, resource allocation shifts in response to water limitation, and local adaptation to the environmental gradient which describes the source locations for native and invasive populations of diffuse knapweed (Centaurea diffusa). Plants were grown in an experimental field in France (naturalized range) under water addition and limitation conditions. After accounting for phenotypic variation arising from environmental differences among collection locations, we found evidence of genetic variation between the invasive and native populations for most morphological and life-history traits under study. Invasive C. diffusa populations produced larger, later maturing, and therefore potentially fitter individuals than native populations. Evidence for local adaptation along a resource allocation trade-off for water limitation tolerance is equivocal. However, native populations do show evidence of local adaptation to an environmental gradient, a relationship which is typically not observed in the invaded range. Broader analysis of the climatic niche inhabited by the species in both ranges suggests that the physiological tolerances of C. diffusa may have expanded in the invaded range. This observation could be due to selection for plastic, "general-purpose" genotypes with broad environmental tolerances.

Inferring population decline and expansion from microsatellite data: a simulation-based evaluation of the Msvar method.

Reconstructing the demographic history of populations is a central issue in evolutionary biology. Using likelihood-based methods coupled with Monte Carlo simulations, it is now possible to reconstruct past changes in population size from genetic data. Using simulated data sets under various demographic scenarios, we evaluate the statistical performance of Msvar, a full-likelihood Bayesian method that infers past demographic change from microsatellite data. Our simulation tests show that Msvar is very efficient at detecting population declines and expansions, provided the event is neither too weak nor too recent. We further show that Msvar outperforms two moment-based methods (the M-ratio test and Bottleneck) for detecting population size changes, whatever the time and the severity of the event. The same trend emerges from a compilation of empirical studies. The latest version of Msvar provides estimates of the current and the ancestral population size and the time since the population started changing in size. We show that, in the absence of prior knowledge, Msvar provides little information on the mutation rate, which results in biased estimates and/or wide credibility intervals for each of the demographic parameters. However, scaling the population size parameters with the mutation rate and scaling the time with current population size, as coalescent theory requires, significantly improves the quality of the estimates for contraction but not for expansion scenarios. Finally, our results suggest that Msvar is robust to moderate departures from a strict stepwise mutation model.

Prediction of extinction in plants: interaction of extrinsic threats and life history traits.

The global extinction of species proceeds through the erosion of local populations. Using a 60-year time series of annual sighting records of plant species, we studied the correlates of local extinction risk associated with a risk of species extinction in the Park Grass Experiment where plants received long-term exposure to nutrient enrichment, soil acidification, and reductions in habitat size. We used multivariate linear models to assess how extrinsic threats and life history traits influence extinction risk. We investigated effects of four extrinsic threats (nitrogen enrichment, productivity, acidification, and plot size) as well as 11 life history traits (month of earliest flowering, flowering duration, stress tolerance, ruderalness [plant species' ability to cope with habitat disturbance], plant height, diaspore mass, seed bank, life form, dispersal mode, apomixis [the ability for a species to reproduce asexuall through seeds], and mating system). Extinction risk was not influenced by plant family. All of the 11 life history traits except life form and all threat variables influenced extinction risk but always via interactions which typically involved one threat variable and one life history trait. We detected comparatively few significant interactions between life history traits, and the interacting traits compensated for each other. These results suggest that simple predictions about extinction risk based on species' traits alone will often fail. In contrast, understanding the interactions between extrinsic threats and life history traits will allow us to make more accurate predictions of extinctions.

Fine-scale genetic structure and gene dispersal in Centaurea corymbosa (Asteraceae). II. Correlated paternity within and among sibships.

The fine-scale pattern of correlated paternity was characterized within a population of the narrow-endemic model plant species, Centaurea corymbosa, using microsatellites and natural progeny arrays. We used classical approaches to assess correlated mating within sibships and developed a new method based on pairwise kinship coefficients to assess correlated paternity within and among sibships in a spatio-temporal perspective. We also performed numerical simulations to assess the relative significance of different mechanisms promoting correlated paternity and to compare the statistical properties of different estimators of correlated paternity. Our new approach proved very informative to assess which factors contributed most to correlated paternity and presented good statistical properties. Within progeny arrays, we found that about one-fifth of offspring pairs were full-sibs. This level of correlated mating did not result from correlated pollen dispersal events (i.e., pollen codispersion) but rather from limited mate availability, the latter being due to limited pollen dispersal distances, the heterogeneity of pollen production among plants, phenological heterogeneity and, according to simulations, the self-incompatibility system. We point out the close connection between correlated paternity and the "TwoGener" approach recently developed to infer pollen dispersal and discuss the conditions to be met when applying the latter.

Microsatellite allele sizes: a simple test to assess their significance on genetic differentiation.

The mutation process at microsatellite loci typically occurs at high rates and with stepwise changes in allele sizes, features that may introduce bias when using classical measures of population differentiation based on allele identity (e.g., F(ST), Nei's Ds genetic distance). Allele size-based measures of differentiation, assuming a stepwise mutation process [e.g., Slatkin's R(ST), Goldstein et al.'s (deltamu)(2)], may better reflect differentiation at microsatellite loci, but they suffer high sampling variance. The relative efficiency of allele size- vs. allele identity-based statistics depends on the relative contributions of mutations vs. drift to population differentiation. We present a simple test based on a randomization procedure of allele sizes to determine whether stepwise-like mutations contributed to genetic differentiation. This test can be applied to any microsatellite data set designed to assess population differentiation and can be interpreted as testing whether F(ST) = R(ST). Computer simulations show that the test efficiently identifies which of F(ST) or R(ST) estimates has the lowest mean square error. A significant test, implying that R(ST) performs better than F(ST), is obtained when the mutation rate, mu, for a stepwise mutation process is (a) >/= m in an island model (m being the migration rate among populations) or (b) >/= 1/t in the case of isolated populations (t being the number of generations since population divergence). The test also informs on the efficiency of other statistics used in phylogenetical reconstruction [e.g., Ds and (deltamu)(2)], a nonsignificant test meaning that allele identity-based statistics perform better than allele size-based ones. This test can also provide insights into the evolutionary history of populations, revealing, for example, phylogeographic patterns, as illustrated by applying it on three published data sets.