Correction: Incomplete dominance of deleterious alleles contributes substantially to trait variation and heterosis in maize.

[This corrects the article DOI: 10.1371/journal.pgen.1007019.].

Incomplete dominance of deleterious alleles contributes substantially to trait variation and heterosis in maize.

Deleterious alleles have long been proposed to play an important role in patterning phenotypic variation and are central to commonly held ideas explaining the hybrid vigor observed in the offspring of a cross between two inbred parents. We test these ideas using evolutionary measures of sequence conservation to ask whether incorporating information about putatively deleterious alleles can inform genomic selection (GS) models and improve phenotypic prediction. We measured a number of agronomic traits in both the inbred parents and hybrids of an elite maize partial diallel population and re-sequenced the parents of the population. Inbred elite maize lines vary for more than 350,000 putatively deleterious sites, but show a lower burden of such sites than a comparable set of traditional landraces. Our modeling reveals widespread evidence for incomplete dominance at these loci, and supports theoretical models that more damaging variants are usually more recessive. We identify haplotype blocks using an identity-by-decent (IBD) analysis and perform genomic prediction analyses in which we weigh blocks on the basis of complementation for segregating putatively deleterious variants. Cross-validation results show that incorporating sequence conservation in genomic selection improves prediction accuracy for grain yield and other fitness-related traits as well as heterosis for those traits. Our results provide empirical support for an important role for incomplete dominance of deleterious alleles in explaining heterosis and demonstrate the utility of incorporating functional annotation in phenotypic prediction and plant breeding.

African Orphan Crops Consortium (AOCC): status of developing genomic resources for African orphan crops.

MAIN CONCLUSION: The African Orphan Crops Consortium (AOCC) successfully initiated the ambitious genome sequencing project of 101 African orphan crops/trees with 6 genomes sequenced, 6 near completion, and 20 currently in progress. Addressing stunting, malnutrition, and hidden hunger through nutritious, economic, and resilient agri-food system is one of the major agricultural challenges of this century. As sub-Saharan Africa harbors a large portion of the severely malnourished population, the African Orphan Crops Consortium (AOCC) was established in 2011 with an aim to reduce stunting and malnutrition by providing nutritional security through improving locally adapted nutritious, but neglected, under-researched or orphan African food crops. Foods from these indigenous or naturalized crops and trees are rich in minerals, vitamins, and antioxidant, and are an integral part of the dietary portfolio and cultural, social, and economic milieu of African farmers. Through stakeholder consultations supported by the African Union, 101 African orphan and under-researched crop species were prioritized to mainstream into African agri-food systems. The AOCC, through a network of international-regional-public-private partnerships and collaborations, is generating genomic resources of three types, i.e., reference genome sequence, transcriptome sequence, and re-sequencing 100 accessions/species, using next-generation sequencing (NGS) technology. Furthermore, the University of California Davis African Plant Breeding Academy under the AOCC banner is training 150 lead African scientists to breed high yielding, nutritious, and climate-resilient (biotic and abiotic stress tolerant) crop varieties that meet African farmer and consumer needs. To date, one or more forms of sequence data have been produced for 60 crops. Reference genome sequences for six species have already been published, 6 are almost near completion, and 19 are in progress.

Method to represent the distribution of QTL additive and dominance effects associated with quantitative traits in computer simulation.

BACKGROUND: Computer simulation is a resource which can be employed to identify optimal breeding strategies to effectively and efficiently achieve specific goals in developing improved cultivars. In some instances, it is crucial to assess in silico the options as well as the impact of various crossing schemes and breeding approaches on performance for traits of interest such as grain yield. For this, a means by which gene effects can be represented in the genome model is critical. RESULTS: To address this need, we devised a method to represent the genomic distribution of additive and dominance gene effects associated with quantitative traits. The method, based on meta-analysis of previously-estimated QTL effects following Bennewitz and Meuwissen (J Anim Breed Genet 127:171-9, 2010), utilizes a modified Dirichlet process Gaussian mixture model (DPGMM) to fit the number of mixture components and estimate parameters (i.e. mean and variance) of the genomic distribution. The method was demonstrated using several maize QTL data sets to provide estimates of additive and dominance effects for grain yield and other quantitative traits for application in maize genome simulations. CONCLUSIONS: The DPGMM method offers an alternative to the over-simplified infinitesimal model in computer simulation as a means to better represent the genetic architecture of quantitative traits, which likely involve some large effects in addition to many small effects. Furthermore, it confers an advantage over other methods in that the number of mixture model components need not be known a priori. In addition, the method is robust with use of large-scale, multi-allelic data sets or with meta-analyses of smaller QTL data sets which may be derived from bi-parental populations in precisely estimating distribution parameters. Thus, the method has high utility in representing the genetic architecture of quantitative traits in computer simulation.

Expression of Nutritional Traits in Vegetable Cowpea Grown under Various South African Agro-Ecological Conditions.

Cowpea (Vigna unguiculata L.), a traditional legume food crop indigenous to Africa, has potential as both a vegetable and grain crop in contributing to dietary diversity to support health and address malnutrition, especially for those relying heavily on wheat, maize, and rice. The expression of nutritional traits (protein content and concentrations of iron (Fe), zinc (Zn), and manganese (Mn)) in cowpea leaves was evaluated over diverse agro-ecologies of South Africa and typical agronomic practices of smallholder farmers. The genotypes evaluated displayed genetic variation for all four traits. The mean values of Fe, Zn, Mn and protein content varied from 33.11 to 69.03 mg.100.g-1; 4.00 to 4.70 mg.100.g-1; and 14.40 to 19.63 mg.100.g-1 and 27.98 to 31.98%, respectively. The correlation analysis revealed significant degree of positive association between protein and Zn (r = 0.20), while negative associations were observed between Mn and protein (-0.46) and between Mn and Fe (r = -0.27). Furthermore, the expression of these important nutrient traits was influenced by the climatic conditions represented by six environments (location by year combinations) as is typical of 'quality' traits. Additionally, genotype-by-environment interaction effects were detected, suggesting that local soil properties and soil health may play a role in nutritional content in plants, perhaps particularly for legume crops that rely on symbiotic relationships with soil bacterial populations to fix nitrogen, which is crucial to protein formation. Further studies are needed to understand how to coordinate and align agronomic and soil management practices in vegetable cowpea production, especially those workable for the smallholder farmer, to realize the full genetic potential and nutritional value of improved vegetable cowpea varieties.

Amaranths.

Chance W. Riggins and Rita H. Mumm introduce the ancient amaranth genus, highlighting the ancient crop's controversial history and its contemporary use in improving food security.

Quantitative Genetic Analysis of Hydroxycinnamic Acids in Maize (Zea mays L.) for Plant Improvement and Production of Health-Promoting Compounds.

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.

High-throughput, Microscale Protocol for the Analysis of Processing Parameters and Nutritional Qualities in Maize (Zea mays L.).

Maize is an important grain crop in the United States and worldwide. However, maize grain must be processed prior to human consumption. Furthermore, whole grain composition and processing characteristics vary among maize hybrids and can impact the quality of the final processed product. Therefore, in order to produce healthier processed food products from maize, it is necessary to know how to optimize processing parameters for particular sets of germplasm to account for these differences in grain composition and processing characteristics. This includes a better understanding of how current processing techniques impact the nutritional quality of the final processed food product. Here, we describe a microscale protocol that both simulates the processing pipeline to produce cornflakes from large flaking grits and allows for the processing of multiple grain samples simultaneously. The flaking grits, the intermediate processed products, or final processed product, as well as the corn grain itself, can be analyzed for nutritional content as part of a high-throughput analytical pipeline. This procedure was developed specifically for incorporation into a maize breeding research program, and it can be modified for other grain crops. We provide an example of the analysis of insoluble-bound ferulic acid and p-coumaric acid content in maize. Samples were taken at five different processing stages. We demonstrate that sampling can take place at multiple stages during microscale processing, that the processing technique can be utilized in the context of a specialized maize breeding program, and that, in our example, most of the nutritional content was lost during food product processing.

Changes in Phenolic Acid Content in Maize during Food Product Processing.

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.

A roadmap for breeding orphan leafy vegetable species: a case study of Gynandropsis gynandra (Cleomaceae).

Despite an increasing awareness of the potential of "orphan" or unimproved crops to contribute to food security and enhanced livelihoods for farmers, coordinated research agendas to facilitate production and use of orphan crops by local communities are generally lacking. We provide an overview of the current knowledge on leafy vegetables with a focus on Gynandropsis gynandra, a highly nutritious species used in Africa and Asia, and highlight general and species-specific guidelines for participatory, genomics-assisted breeding of orphan crops. Key steps in genome-enabled orphan leafy vegetables improvement are identified and discussed in the context of Gynandropsis gynandra breeding, including: (1) germplasm collection and management; (2) product target definition and refinement; (3) characterization of the genetic control of key traits; (4) design of the 'process' for cultivar development; (5) integration of genomic data to optimize that 'process'; (6) multi-environmental participatory testing and end-user evaluation; and (7) crop value chain development. The review discusses each step in detail, with emphasis on improving leaf yield, phytonutrient content, organoleptic quality, resistance to biotic and abiotic stresses and post-harvest management.

Concentration of Beneficial Phytochemicals in Harvested Grain of U.S. Yellow Dent Maize (Zea mays L.) Germplasm.

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.

Optimized breeding strategies for multiple trait integration: III. Parameters for success in version testing.

Multiple trait integration (MTI) is the process by which a target hybrid (or variety) is converted to add value-added traits to the comprehensive performance package represented by that genotype. The goal is to recover all the attributes of the target hybrid, with the addition of the specified value-added traits. In maize, this process utilizes the backcross breeding method to incorporate transgenic events (or genes) of interest. Thus, MTI involves four main steps: single event introgression, event pyramiding, trait fixation, and version testing to ensure recovery of equivalent performance with at least one version of the converted hybrid. Based on a case study involving conversion of a target hybrid for 15 transgenic events (the female inbred parent was converted for 8 events, and the male inbred parent was converted for 7 events), we explored parameters in version testing to facilitate a high likelihood of recovering at least one version of the hybrid conversion with yield performance equivalency within 3 % of unconverted target hybrid. Using computer simulation, we explored the impact of two factors on the success rate of the MTI outcome: (1) the amount of residual NRP (non-recurrent parent) germplasm remaining in the converted hybrid and (2) the number of versions of each parental line conversion created. A range of residual NRP germplasm from 120 to 180 cM (which represents 95.0-96.6 % germplasm recovery of the target hybrid in maize) and up to 5 versions of each parental conversion were considered, with all possible hybrid combinations of each version of female and male RP (recurrent parent) conversion evaluated for yield. With 5 versions of each RP conversion and testing of 25 hybrid versions, a >95 % rate of success was realized when the amount of residual NRP germplasm in the hybrid conversion was ≤180 cM. When hybrid conversions contained ≤120-cM residual NRP germplasm, only 4 versions of one of the parental conversions were needed (rather than 5), requiring 20 versions of the hybrid conversion to be yield tested. These results have implications in the strategic design of an overall conversion program and for the upstream MTI process, especially in setting thresholds for the amount of NRP germplasm remaining in RP conversions. Furthermore, these results validate findings of (Peng et al. in Mol Breed 33:189-104, 2014a. doi:10.1007/s11032-013-9936-7, in Mole Breed 33:105-115, 2014b. doi:10.1007/s11032-013-9937-6) which outline effective breeding strategies to optimize earlier steps in MTI (preceding version testing).

Optimized breeding strategies for multiple trait integration: I. Minimizing linkage drag in single event introgression.

From a breeding standpoint, multiple trait integration (MTI) is a four-step process of converting an elite variety/hybrid for value-added traits (e.g. transgenic events) using backcross breeding, ultimately regaining the performance attributes of the target hybrid along with reliable expression of the value-added traits. In the light of the overarching goal of recovering equivalent performance in the finished conversion, this study focuses on the first step of MTI, single event introgression, exploring the feasibility of marker-aided backcross conversion of a target maize hybrid for 15 transgenic events, incorporating eight events into the female hybrid parent and seven into the male parent. Single event introgression is conducted in parallel streams to convert the recurrent parent (RP) for individual events, with the primary objective of minimizing residual non-recurrent parent (NRP) germplasm, especially in the chromosomal proximity to the event (i.e. linkage drag). In keeping with a defined lower limit of 96.66 % overall RP germplasm recovery (i.e. ≤120 cM NRP germplasm given a genome size of 1,788 cM), a breeding goal for each of the 15 single event conversions was developed: <8 cM of residual NRP germplasm across the genome with ~1 cM in the 20 cM region flanking the event. Using computer simulation, we aimed to identify optimal breeding strategies for single event introgression to achieve this breeding goal, measuring efficiency in terms of number of backcross generations required, marker data points needed, and total population size across generations. Various selection schemes classified as three-stage, modified two-stage, and combined selection conducted from BC1 through BC3, BC4, or BC5 were compared. The breeding goal was achieved with a selection scheme involving five generations of marker-aided backcrossing, with BC1 through BC3 selected for the event of interest and minimal linkage drag at population size of 600, and BC4 and BC5 selected for the event of interest and recovery of the RP germplasm across the genome at population size of 400, with selection intensity of 0.01 for all generations. In addition, strategies for choice of donor parent to facilitate conversion efficiency and quality were evaluated. Two essential criteria for choosing an optimal donor parent for a given RP were established: introgression history showing reduction of linkage drag to ~1 cM in the 20 cM region flanking the event and genetic similarity between the RP and potential donor parents. Computer simulation demonstrated that single event conversions with <8 cM residual NRP germplasm can be accomplished by BC5 with no genetic similarity, by BC4 with 30 % genetic similarity, and by BC3 with 86 % genetic similarity using previously converted RPs as event donors. This study indicates that MTI to produce a 'quality' 15-event-stacked hybrid conversion is achievable. Furthermore, it lays the groundwork for a comprehensive approach to MTI by outlining a pathway to produce appropriate starting materials with which to proceed with event pyramiding and trait fixation before version testing.

Optimized breeding strategies for multiple trait integration: II. Process efficiency in event pyramiding and trait fixation.

Multiple trait integration (MTI) is a multi-step process of converting an elite variety/hybrid for value-added traits (e.g. transgenic events) through backcross breeding. From a breeding standpoint, MTI involves four steps: single event introgression, event pyramiding, trait fixation, and version testing. This study explores the feasibility of marker-aided backcross conversion of a target maize hybrid for 15 transgenic events in the light of the overall goal of MTI of recovering equivalent performance in the finished hybrid conversion along with reliable expression of the value-added traits. Using the results to optimize single event introgression (Peng et al. Optimized breeding strategies for multiple trait integration: I. Minimizing linkage drag in single event introgression. Mol Breed, 2013) which produced single event conversions of recurrent parents (RPs) with ≤8 cM of residual non-recurrent parent (NRP) germplasm with ~1 cM of NRP germplasm in the 20 cM regions flanking the event, this study focused on optimizing process efficiency in the second and third steps in MTI: event pyramiding and trait fixation. Using computer simulation and probability theory, we aimed to (1) fit an optimal breeding strategy for pyramiding of eight events into the female RP and seven in the male RP, and (2) identify optimal breeding strategies for trait fixation to create a 'finished' conversion of each RP homozygous for all events. In addition, next-generation seed needs were taken into account for a practical approach to process efficiency. Building on work by Ishii and Yonezawa (Optimization of the marker-based procedures for pyramiding genes from multiple donor lines: I. Schedule of crossing between the donor lines. Crop Sci 47:537-546, 2007a), a symmetric crossing schedule for event pyramiding was devised for stacking eight (seven) events in a given RP. Options for trait fixation breeding strategies considered selfing and doubled haploid approaches to achieve homozygosity as well as seed chipping and tissue sampling approaches to facilitate genotyping. With selfing approaches, two generations of selfing rather than one for trait fixation (i.e. 'F2 enrichment' as per Bonnett et al. in Strategies for efficient implementation of molecular markers in wheat breeding. Mol Breed 15:75-85, 2005) were utilized to eliminate bottlenecking due to extremely low frequencies of desired genotypes in the population. The efficiency indicators such as total number of plants grown across generations, total number of marker data points, total number of generations, number of seeds sampled by seed chipping, number of plants requiring tissue sampling, and number of pollinations (i.e. selfing and crossing) were considered in comparisons of breeding strategies. A breeding strategy involving seed chipping and a two-generation selfing approach (SC + SELF) was determined to be the most efficient breeding strategy in terms of time to market and resource requirements. Doubled haploidy may have limited utility in trait fixation for MTI under the defined breeding scenario. This outcome paves the way for optimizing the last step in the MTI process, version testing, which involves hybridization of female and male RP conversions to create versions of the converted hybrid for performance evaluation and possible commercial release.

Land usage attributed to corn ethanol production in the United States: sensitivity to technological advances in corn grain yield, ethanol conversion, and co-product utilization.

BACKGROUND: Although the system for producing yellow corn grain is well established in the US, its role among other biofeedstock alternatives to petroleum-based energy sources has to be balanced with its predominant purpose for food and feed as well as economics, land use, and environmental stewardship. We model land usage attributed to corn ethanol production in the US to evaluate the effects of anticipated technological change in corn grain production, ethanol processing, and livestock feeding through a multi-disciplinary approach. Seven scenarios are evaluated: four considering the impact of technological advances on corn grain production, two focused on improved efficiencies in ethanol processing, and one reflecting greater use of ethanol co-products (that is, distillers dried grains with solubles) in diets for dairy cattle, pigs, and poultry. For each scenario, land area attributed to corn ethanol production is estimated for three time horizons: 2011 (current), the time period at which the 15 billion gallon cap for corn ethanol as per the Renewable Fuel Standard is achieved, and 2026 (15 years out). RESULTS: Although 40.5% of corn grain was channeled to ethanol processing in 2011, only 25% of US corn acreage was attributable to ethanol when accounting for feed co-product utilization. By 2026, land area attributed to corn ethanol production is reduced to 11% to 19% depending on the corn grain yield level associated with the four corn production scenarios, considering oil replacement associated with the soybean meal substituted in livestock diets with distillers dried grains with solubles. Efficiencies in ethanol processing, although producing more ethanol per bushel of processed corn, result in less co-products and therefore less offset of corn acreage. Shifting the use of distillers dried grains with solubles in feed to dairy cattle, pigs, and poultry substantially reduces land area attributed to corn ethanol production. However, because distillers dried grains with solubles substitutes at a higher rate for soybean meal, oil replacement requirements intensify and positively feedback to elevate estimates of land usage. CONCLUSIONS: Accounting for anticipated technological changes in the corn ethanol system is important for understanding the associated land base ascribed, and may aid in calibrating parameters for land use models in biofuel life-cycle analyses.

A look at product development with genetically modified crops: examples from maize.

Plant breeding for crop genetic improvement involves the cycle of creating genetic diversity and exploiting that diversity to derive an improved cultivar with outstanding performance for specific traits of interest. Genetic modification through transformation essentially expands the genepool to facilitate access to genes otherwise not available through crossing. Transgenic events are defined by the DNA sequence that has been incorporated into the target genome and the specific point(s) of insertion. In the development of a new transgenic trait, typically many events are generated and evaluated with the aim of identifying one exhibiting consistent trait expression at or above specified thresholds, stable inheritance, and the absence of any negative effects. With transgenic traits for maize, once commercial candidates have been identified, these events are introgressed into elite lines, often through the use of molecular markers that can accelerate the breeding process and aid in producing a quality conversion. Converted elite lines are yield-tested to ensure performance equivalency with their unconverted counterparts. Finally, before commercial sale of seed, quality control monitoring is conducted to ensure event identity and purity and the absence of any unintended events. This monitoring complements other quality control measures to confirm seed viability and line/hybrid purity and uniformity in seed treatments, all in an effort to ensure customer satisfaction and to comply with governmental regulations. Thus, genetically modified (GM) cultivars are subject to significant testing and auditing prior to seed sale and distribution to farmers, more testing and auditing than with non-GM cultivars.

Nonparametric method for genomics-based prediction of performance of quantitative traits involving epistasis in plant breeding.

Genomic selection (GS) procedures have proven useful in estimating breeding value and predicting phenotype with genome-wide molecular marker information. However, issues of high dimensionality, multicollinearity, and the inability to deal effectively with epistasis can jeopardize accuracy and predictive ability. We, therefore, propose a new nonparametric method, pRKHS, which combines the features of supervised principal component analysis (SPCA) and reproducing kernel Hilbert spaces (RKHS) regression, with versions for traits with no/low epistasis, pRKHS-NE, to high epistasis, pRKHS-E. Instead of assigning a specific relationship to represent the underlying epistasis, the method maps genotype to phenotype in a nonparametric way, thus requiring fewer genetic assumptions. SPCA decreases the number of markers needed for prediction by filtering out low-signal markers with the optimal marker set determined by cross-validation. Principal components are computed from reduced marker matrix (called supervised principal components, SPC) and included in the smoothing spline ANOVA model as independent variables to fit the data. The new method was evaluated in comparison with current popular methods for practicing GS, specifically RR-BLUP, BayesA, BayesB, as well as a newer method by Crossa et al., RKHS-M, using both simulated and real data. Results demonstrate that pRKHS generally delivers greater predictive ability, particularly when epistasis impacts trait expression. Beyond prediction, the new method also facilitates inferences about the extent to which epistasis influences trait expression.