Recruitment of microorganisms to the rhizosphere varies among plant genotypes, yet an understanding of whether the microbiome can be altered by selection on the host is relatively unknown. Here, we ...performed a common garden study to characterize recruitment of rhizosphere microbiome, functional groups, for 20 expired Plant Variety Protection Act maize lines spanning a chronosequence of development from 1949 to 1986. This time frame brackets a series of agronomic innovations, namely improvements in breeding and the application of synthetic nitrogenous fertilizers, technologies that define modern industrial agriculture. We assessed the impact of chronological agronomic improvements on recruitment of the rhizosphere microbiome in maize, with emphasis on nitrogen cycling functional groups. In addition, we quantified the microbial genes involved in nitrogen cycling and predicted functional pathways present in the microbiome of each genotype. Both genetic relatednesses of host plant and decade of germplasm development were significant factors in the recruitment of the rhizosphere microbiome. More recently developed germplasm recruited fewer microbial taxa with the genetic capability for sustainable nitrogen provisioning and larger populations of microorganisms that contribute to N losses. This study indicates that the development of high-yielding varieties and agronomic management approaches of industrial agriculture inadvertently modified interactions between maize and its microbiome.
The western corn rootworm, Diabrotica virgifera virgifera LeConte, is an established insect pest of maize (Zea mays L.) in North America. The rotation of maize with another crop, principally ...soybeans, Glycine max (L.), was the primary management strategy utilized by North American producers and remained highly effective until the mid-1990s. In 1995, widespread and severe root injury occurred in east-central Illinois and northern Indiana maize fields that had been annually rotated with soybeans on a regular basis for several decades. The failure of this cultural tactic from a pest management perspective was attributed to a behavioral adaptation by a variant western corn rootworm that had lost fidelity to maize for egg laying. In 1992, an infestation of western corn rootworm was found within a small maize field near the Belgrade Airport. By 2007, the presence of this insect pest had been confirmed in 20 European countries. More recent molecular studies have confirmed that at least three separate invasions (until 2004) of western corn rootworms have occurred in Europe, increasing the risk that rotation-resistant western corn rootworms will be introduced into a new continent. Although biological control and use of conventional resistant maize hybrids have not achieved widespread success in the management of western corn rootworms in North America, these tactics are being evaluated in Europe.
Prediction of single-cross performance has been a major goal of plant breeders since the beginning of hybrid breeding. Recently, genomic prediction has shown to be a promising approach, but only ...limited studies have examined the accuracy of predicting single-cross performance. Moreover, no studies have examined the potential of predicting single crosses among random inbreds derived from a series of biparental families, which resembles the structure of germplasm comprising the initial stages of a hybrid maize breeding pipeline. The main objectives of this study were to evaluate the potential of genomic prediction for identifying superior single crosses early in the hybrid breeding pipeline and optimize its application. To accomplish these objectives, we designed and analyzed a novel population of single crosses representing the Iowa Stiff Stalk synthetic/non-Stiff Stalk heterotic pattern commonly used in the development of North American commercial maize hybrids. The performance of single crosses was predicted using parental combining ability and covariance among single crosses. Prediction accuracies were estimated using cross-validation and ranged from 0.28 to 0.77 for grain yield, 0.53 to 0.91 for plant height, and 0.49 to 0.94 for staygreen, depending on the number of tested parents of the single cross and genomic prediction method used. The genomic estimated general and specific combining abilities showed an advantage over genomic covariances among single crosses when one or both parents of the single cross were untested. Overall, our results suggest that genomic prediction of single crosses in the early stages of a hybrid breeding pipeline holds great potential to redesign hybrid breeding and increase its efficiency.
Hydroxycinnamic acids, including ferulic acid and p-coumaric acid, have been tied to multiple positive health and agronomic benefits. However, little work has been done to improve the concentration ...of hydroxycinnamic acids in maize. We evaluated a set of 12 commercially important maize (Zea mays L.) inbred lines and 66 hybrids derived from their crosses for hydroxycinnamic acid concentration in the grain, grain yield, and test weight. The grain was obtained from replicated field experiments, which were conducted for 3 years. Both ferulic acid and p-coumaric acid were found to be highly heritable, and most of the genetic variation was additive. Grain yield and test weight were not correlated with hydroxycinnamic acid concentration. These findings suggest that breeding maize for improved hydroxycinnamic acid concentration is feasible. Maize hybrids with high hydroxycinnamic acid concentrations in the grain could be useful for the production of dietary supplements or all-natural food additives while imparting enhanced resistance to biotic and abiotic stresses during the growing season and grain storage.
Key message
We demonstrate potential for improved multi-environment genomic prediction accuracy using structural variant markers. However, the degree of observed improvement is highly dependent on ...the genetic architecture of the trait.
Breeders commonly use genetic markers to predict the performance of untested individuals as a way to improve the efficiency of breeding programs. These genomic prediction models have almost exclusively used single nucleotide polymorphisms (SNPs) as their source of genetic information, even though other types of markers exist, such as structural variants (SVs). Given that SVs are associated with environmental adaptation and not all of them are in linkage disequilibrium to SNPs, SVs have the potential to bring additional information to multi-environment prediction models that are not captured by SNPs alone. Here, we evaluated different marker types (SNPs and/or SVs) on prediction accuracy across a range of genetic architectures for simulated traits across multiple environments. Our results show that SVs can improve prediction accuracy, but it is highly dependent on the genetic architecture of the trait and the relative gain in accuracy is minimal. When SVs are the only causative variant type, 70% of the time SV predictors outperform SNP predictors. However, the improvement in accuracy in these instances is only 1.5% on average. Further simulations with predictors in varying degrees of LD with causative variants of different types (e.g., SNPs, SVs, SNPs and SVs) showed that prediction accuracy increased as linkage disequilibrium between causative variants and predictors increased regardless of the marker type. This study demonstrates that knowing the genetic architecture of a trait in deciding what markers to use in large-scale genomic prediction modeling in a breeding program is more important than what types of markers to use.
Although previous studies have examined the concentration of various nutritional compounds in maize, little focus has been devoted to the study of commercial maize hybrids or their inbred parents. In ...this study, a genetically and phenotypically diverse set of maize hybrids and inbreds relevant to U.S. commercial maize germplasm was evaluated for its variability in phytochemical content. Total protein, unsaturated fatty acids, tocopherols, soluble phenolics, and insoluble-bound phenolics were evaluated in this study. Of these compounds, only soluble and insoluble-bound phenolic acids exhibited means and variances that were at least as large as the means and variances reported for other sets of germplasm. This suggests that selection for high phenolic acid content is possible in current U.S. commercial germplasm. In contrast, while the total protein, unsaturated fatty acid, or tocopherol content could possibly be improved using current U.S. commercial germplasm, the results of this study indicate that the incorporation of more diverse sources of germplasm would most likely result in quicker genetic gains.
Abstract
Understanding how plants adapt to specific environmental changes and identifying genetic markers associated with phenotypic plasticity can help breeders develop plant varieties adapted to a ...rapidly changing climate. Here, we propose the use of marker effect networks as a novel method to identify markers associated with environmental adaptability. These marker effect networks are built by adapting commonly used software for building gene coexpression networks with marker effects across growth environments as the input data into the networks. To demonstrate the utility of these networks, we built networks from the marker effects of ∼2,000 nonredundant markers from 400 maize hybrids across 9 environments. We demonstrate that networks can be generated using this approach, and that the markers that are covarying are rarely in linkage disequilibrium, thus representing higher biological relevance. Multiple covarying marker modules associated with different weather factors throughout the growing season were identified within the marker effect networks. Finally, a factorial test of analysis parameters demonstrated that marker effect networks are relatively robust to these options, with high overlap in modules associated with the same weather factors across analysis parameters. This novel application of network analysis provides unique insights into phenotypic plasticity and specific environmental factors that modulate the genome.
Plants have a surprising capacity to alter their environmental conditions to create adequate niches for survival and stress tolerance. This process of environmental transformation, commonly referred ...to as “extended phenotypes” or “niche construction”, has historically been studied in the domain of ecology, but this is a process that is pervasive across the plant kingdom. Furthermore, research is beginning to show that plants’ extended phenotypes shape the assembly and function of closely associated microbial communities. Incorporation and understanding the role that plant-extended phenotypes play in agriculture may offer novel, bioinspired methods to manage our arable soil microbiomes. Here, we review the challenges agriculture faces, the plant extended phenotypes we know to shape the microbiome, and the potential utilization of this knowledge to improve the environmental impact of agriculture. Understanding how plant extended phenotypes shape microbial communities could be a key to creating a sustainable future with both plants and microbiomes in consideration.
The notion that many nutrients and beneficial phytochemicals in maize are lost due to food product processing is common, but this has not been studied in detail for the phenolic acids. Information ...regarding changes in phenolic acid content throughout processing is highly valuable because some phenolic acids are chemopreventive agents of aging-related diseases. It is unknown when and why these changes in phenolic acid content might occur during processing, whether some maize genotypes might be more resistant to processing induced changes in phenolic acid content than other genotypes, or if processing affects the bioavailability of phenolic acids in maize-based food products. For this study, a laboratory-scale processing protocol was developed and used to process whole maize kernels into toasted cornflakes. High-throughput microscale wet-lab analyses were applied to determine the concentrations of soluble and insoluble-bound phenolic acids in samples of grain, three intermediate processing stages, and toasted cornflakes obtained from 12 ex-PVP maize inbreds and seven hybrids. In the grain, insoluble-bound ferulic acid was the most common phenolic acid, followed by insoluble-bound p-coumaric acid and soluble cinnamic acid, a precursor to the phenolic acids. Notably, the ferulic acid content was approximately 1950 μg/g, more than ten-times the concentration of many fruits and vegetables. Processing reduced the content of the phenolic acids regardless of the genotype. Most changes occurred during dry milling due to the removal of the bran. The concentration of bioavailable soluble ferulic and p-coumaric acid increased negligibly due to thermal stresses. Therefore, the current dry milling based processing techniques used to manufacture many maize-based foods, including breakfast cereals, are not conducive for increasing the content of bioavailable phenolics in processed maize food products. This suggests that while maize is an excellent source of phenolics, alternative or complementary processing methods must be developed before this nutritional resource can be utilized.
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•We documented the impact of root architecture on entomopathogenic nematodes behavior.•Increasing complexity of model-roots reduced the performances of the nematodes.•Root volatiles ...significantly led nematodes in the vicinity model-roots, even with high architectural complexity.•Nematodes also moved along natural root systems.•Root architecture not only impacts plants but also upper trophic levels.
As obligate parasites, entomopathogenic nematodes (EPN) rely on insect hosts to complete their development. In insect pest management, EPN infectiousness has varied a lot. A better understanding of their host-finding behavior in the rhizosphere is therefore crucial to enhance EPN potential in biological control. As previously demonstrated, roots can be used as a pathway to insect hosts by EPN, but this interaction and its impact on EPN foraging remain poorly documented. Three artificial model-roots with different degrees of complexity and connectivity were designed to investigate the impact of root architecture on foraging behavior of the EPN Heterorhabditis megidis. Insect baits were placed at the bottom of each model-root that was subsequently buried in moist sand. After injection of the EPN, the number of EPN-infected baits as well as the number of mature nematodes inside each individual carcass was recorded. The influence of insect-induced root volatiles was also evaluated by spiking the baits with a synthetic version of a natural insect-induced root cue. The ecological relevance of the results was tested in soil with two maize genotypes each exhibiting broadly different root architectures. H. megidi performed better in presence of model-roots. Foraging performances of H. megidis declined with the increasing model-root complexity. Adding the synthetic root volatile dramatically changed this pattern and favored the EPN on the most complex model-roots. H. megidis also moved in the vicinity of maize roots to find the insect baits in soil, and natural root architecture also tended to shape H. megidis foraging behavior. This study adds to the scarce body of literature characterizing physical and chemical interactions between EPN and roots. The present data illustrate that root architecture not only modifies plant quality but also shapes upper trophic levels’ ecology.
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