Revisiting hybrid breeding designs using genomic predictions: simulations highlight the superiority of incomplete factorials between segregating families over topcross designs.

KEY MESSAGE: Simulations showed that hybrid performances issued from an incomplete factorial between segregating families of two heterotic groups enable to calibrate genomic predictions of hybrid value more efficiently than tester-based designs. Genomic selection offers new opportunities to revisit hybrid breeding by replacing extensive phenotyping of hybrid combinations by genomic predictions. A key question remains to identify the best design to calibrate genomic prediction models. We proposed to use single-cross hybrids issued from an incomplete factorial design between segregating populations and compared this strategy with a conventional approach based on topcross evaluation. Two multiparental segregating populations of lines, each specific of one heterotic group, were simulated. Hybrids considered as training sets were generated using either (1) a parental line from the opposite group as tester or (2) following an incomplete factorial design. Different specific combining ability (SCA) proportions were simulated by considering different levels of group divergence and dominance effects for the simulated QTL. For the incomplete factorial design, for a same number of hybrids, we considered different numbers of parental lines and different contributions of lines (one to four) to calibration hybrids. We evaluated for different training set sizes prediction accuracies of new hybrids and genetic gains along three generations. At a given training set size, factorial design was as efficient (considering accuracy) as tester design in additive scenarios, but significantly outperformed tester design when SCA was present. The contribution number of each parental line to the incomplete factorial design had a small impact on accuracies. Our simulations confirmed experimental results and showed that calibrating models on hybrids between two multiparental populations is a cost-efficient way to perform genomic predictions in both groups, opening prospects for revisiting reciprocal recurrent selection schemes.

Predicting genomic selection efficiency to optimize calibration set and to assess prediction accuracy in highly structured populations.

KEY MESSAGE: We propose a criterion to predict genomic selection efficiency for structured populations. This criterion is useful to define optimal calibration set and to estimate prediction reliability for multiparental populations. Genomic selection refers to the use of genotypic information for predicting the performance of selection candidates. It has been shown that prediction accuracy depends on various parameters including the composition of the calibration set (CS). Assessing the level of accuracy of a given prediction scenario is of highest importance because it can be used to optimize CS sampling before collecting phenotypes, and once the breeding values are predicted it informs the breeders about the reliability of these predictions. Different criteria were proposed to optimize CS sampling in highly diverse panels, which can be useful to screen collections of genotypes. But plant breeders often work on structured material such as biparental or multiparental populations, for which these criteria are less adapted. We derived from the generalized coefficient of determination (CD) theory different criteria to optimize CS sampling and to assess the reliability associated to predictions in structured populations. These criteria were evaluated on two nested association mapping (NAM) populations and two highly diverse panels of maize. They were efficient to sample optimized CS in most situations. They could also estimate at least partly the reliability associated to predictions between NAM families, but they could not estimate differences in the reliability associated to the predictions of NAM families using the highly diverse panels as calibration sets. We illustrated that the CD criteria could be adapted to various prediction scenarios including inter and intra-family predictions, resulting in higher prediction accuracies.

Association mapping for phenology and plant architecture in maize shows higher power for developmental traits compared with growth influenced traits.

Plant architecture, phenology and yield components of cultivated plants have repeatedly been shaped by selection to meet human needs and adaptation to different environments. Here we assessed the genetic architecture of 24 correlated maize traits that interact during plant cycle. Overall, 336 lines were phenotyped in a network of 9 trials and genotyped with 50K single-nucleotide polymorphisms. Phenology was the main factor of differentiation between genetic groups. Then yield components distinguished dents from lower yielding genetic groups. However, most of trait variation occurred within group and we observed similar overall and within group correlations, suggesting a major effect of pleiotropy and/or linkage. We found 34 quantitative trait loci (QTLs) for individual traits and six for trait combinations corresponding to PCA coordinates. Among them, only five were pleiotropic. We found a cluster of QTLs in a 5 Mb region around Tb1 associated with tiller number, ear row number and the first PCA axis, the latter being positively correlated to flowering time and negatively correlated to yield. Kn1 and ZmNIP1 were candidate genes for tillering, ZCN8 for leaf number and Rubisco Activase 1 for kernel weight. Experimental repeatabilities, numbers of QTLs and proportion of explained variation were higher for traits related to plant development such as tillering, leaf number and flowering time, than for traits affected by growth such as yield components. This suggests a simpler genetic determinism with larger individual QTL effects for the first category.

General and specific combining abilities in a maize (Zea mays L.) test-cross hybrid panel: relative importance of population structure and genetic divergence between parents.

KEY MESSAGE: General and specific combining abilities of maize hybrids between 288 inbred lines and three tester lines were highly related to population structure and genetic distance inferred from SNP data. Many studies have attempted to provide reliable and quick methods to identify promising parental lines and combinations in hybrid breeding programs. Since the 1950s, maize germplasm has been organized into heterotic groups to facilitate the exploitation of heterosis. Molecular markers have proven efficient tools to address the organization of genetic diversity and the relationship between lines or populations. The aim of the present work was to investigate to what extent marker-based evaluations of population structure and genetic distance may account for general (GCA) and specific (SCA) combining ability components in a population composed of 800 inter and intra-heterotic group hybrids obtained by crossing 288 inbred lines and three testers. Our results illustrate a strong effect of groups identified by population structure analysis on both GCA and SCA components. Including genetic distance between parental lines of hybrids in the model leads to a significant decrease of SCA variance component and an increase in GCA variance component for all the traits. The latter suggests that this approach can be efficient to better estimate the potential combining ability of inbred lines when crossed with unrelated lines, and limits the consequences of tester choice. Significant residual GCA and SCA variance components of models taking into account structure and/or genetic distance highlight the variation available for breeding programs within structure groups.

Dent and Flint maize diversity panels reveal important genetic potential for increasing biomass production.

KEY MESSAGE: Genetic and phenotypic analysis of two complementary maize panels revealed an important variation for biomass yield. Flowering and biomass QTL were discovered by association mapping in both panels. The high whole plant biomass productivity of maize makes it a potential source of energy in animal feeding and biofuel production. The variability and the genetic determinism of traits related to biomass are poorly known. We analyzed two highly diverse panels of Dent and Flint lines representing complementary heterotic groups for Northern Europe. They were genotyped with the 50 k SNP-array and phenotyped as hybrids (crossed to a tester of the complementary pool) in a western European field trial network for traits related to flowering time, plant height, and biomass. The molecular information revealed to be a powerful tool for discovering different levels of structure and relatedness in both panels. This study revealed important variation and potential genetic progress for biomass production, even at constant precocity. Association mapping was run by combining genotypes and phenotypes in a mixed model with a random polygenic effect. This permitted the detection of significant associations, confirming height and flowering time quantitative trait loci (QTL) found in literature. Biomass yield QTL were detected in both panels but were unstable across the environments. Alternative kinship estimator only based on markers unlinked to the tested SNP increased the number of significant associations by around 40% with a satisfying control of the false positive rate. This study gave insights into the variability and the genetic architectures of biomass-related traits in Flint and Dent lines and suggests important potential of these two pools for breeding high biomass yielding hybrid varieties.

Mesenchymal stem cell therapy induces glucocorticoid synthesis in colonic mucosa and suppresses radiation-activated T cells: new insights into MSC immunomodulation.

Non-neoplastic tissues around an abdomino-pelvic tumor can be damaged by the radiotherapy protocol, leading to chronic gastrointestinal complications that affect the quality of life with substantial mortality. Stem cell-based approaches using immunosuppressive bone marrow mesenchymal stem cells (MSCs) are promising cell therapy tools. In a rat model of radiation proctitis, we evidenced that a single MSC injection reduces colonic mucosa damages induced by ionizing radiation with improvement of the re-epithelization process for up to 21 days. Immune cell infiltrate and inflammatory molecule expressions in the colonic mucosa were investigated. We report that MSC therapy specifically reduces T-cell infiltration and proliferation, and increases apoptosis of radiation-activated T cells. We assessed the underlying molecular mechanisms and found that interleukin-10 and regulatory T lymphocytes are not involved in the immunosuppressive process in this model. However, an increased level of corticosterone secretion and HSD11b1 (11ß-hydroxysteroid dehydrogenase type 1)-steroidogenic enzyme expression was detected in colonic mucosa 21 days after MSC treatment. Moreover, blocking the glucocorticoid (GC) receptor using the RU486 molecule statistically enhances the allogenic lymphocyte proliferation inhibited by MSCs in vitro and abrogates the mucosal protection induced by MSC treatment in vivo. Using the irradiation model, we found evidence for a new MSC immunosuppressive mechanism involving GCs.

Combined linkage and linkage disequilibrium QTL mapping in multiple families of maize (Zea mays L.) line crosses highlights complementarities between models based on parental haplotype and single locus polymorphism.

Advancements in genotyping are rapidly decreasing marker costs and increasing marker density. This opens new possibilities for mapping quantitative trait loci (QTL), in particular by combining linkage disequilibrium information and linkage analysis (LDLA). In this study, we compared different approaches to detect QTL for four traits of agronomical importance in two large multi-parental datasets of maize (Zea mays L.) of 895 and 928 testcross progenies composed of 7 and 21 biparental families, respectively, and genotyped with 491 markers. We compared to traditional linkage-based methods two LDLA models relying on the dense genotyping of parental lines with 17,728 SNP: one based on a clustering approach of parental line segments into ancestral alleles and one based on single marker information. The two LDLA models generally identified more QTL (60 and 52 QTL in total) than classical linkage models (49 and 44 QTL in total). However, they performed inconsistently over datasets and traits suggesting that a compromise must be found between the reduction of allele number for increasing statistical power and the adequacy of the model to potentially complex allelic variation. For some QTL, the model exclusively based on linkage analysis, which assumed that each parental line carried a different QTL allele, was able to capture remaining variation not explained by LDLA models. These complementarities between models clearly suggest that the different QTL mapping approaches must be considered to capture the different levels of allelic variation at QTL involved in complex traits.

Out of America: tracing the genetic footprints of the global diffusion of maize.

Maize was first domesticated in a restricted valley in south-central Mexico. It was diffused throughout the Americas over thousands of years, and following the discovery of the New World by Columbus, was introduced into Europe. Trade and colonization introduced it further into all parts of the world to which it could adapt. Repeated introductions, local selection and adaptation, a highly diverse gene pool and outcrossing nature, and global trade in maize led to difficulty understanding exactly where the diversity of many of the local maize landraces originated. This is particularly true in Africa and Asia, where historical accounts are scarce or contradictory. Knowledge of post-domestication movements of maize around the world would assist in germplasm conservation and plant breeding efforts. To this end, we used SSR markers to genotype multiple individuals from hundreds of representative landraces from around the world. Applying a multidisciplinary approach combining genetic, linguistic, and historical data, we reconstructed possible patterns of maize diffusion throughout the world from American "contribution" centers, which we propose reflect the origins of maize worldwide. These results shed new light on introductions of maize into Africa and Asia. By providing a first globally comprehensive genetic characterization of landraces using markers appropriate to this evolutionary time frame, we explore the post-domestication evolutionary history of maize and highlight original diversity sources that may be tapped for plant improvement in different regions of the world.

Maximizing the reliability of genomic selection by optimizing the calibration set of reference individuals: comparison of methods in two diverse groups of maize inbreds (Zea mays L.).

Genomic selection refers to the use of genotypic information for predicting breeding values of selection candidates. A prediction formula is calibrated with the genotypes and phenotypes of reference individuals constituting the calibration set. The size and the composition of this set are essential parameters affecting the prediction reliabilities. The objective of this study was to maximize reliabilities by optimizing the calibration set. Different criteria based on the diversity or on the prediction error variance (PEV) derived from the realized additive relationship matrix-best linear unbiased predictions model (RA-BLUP) were used to select the reference individuals. For the latter, we considered the mean of the PEV of the contrasts between each selection candidate and the mean of the population (PEVmean) and the mean of the expected reliabilities of the same contrasts (CDmean). These criteria were tested with phenotypic data collected on two diversity panels of maize (Zea mays L.) genotyped with a 50k SNPs array. In the two panels, samples chosen based on CDmean gave higher reliabilities than random samples for various calibration set sizes. CDmean also appeared superior to PEVmean, which can be explained by the fact that it takes into account the reduction of variance due to the relatedness between individuals. Selected samples were close to optimality for a wide range of trait heritabilities, which suggests that the strategy presented here can efficiently sample subsets in panels of inbred lines. A script to optimize reference samples based on CDmean is available on request.

Diversity and linkage disequilibrium features in a composite public/private dent maize panel: consequences for association genetics as evaluated from a case study using flowering time.

Recent progress in genotyping and resequencing techniques have opened new opportunities for deciphering quantitative trait variation by looking for associations between traits of interest and polymorphisms in panels of diverse inbred lines. Association mapping raises specific issues related to the choice of appropriate (i) panels and marker-densities and (ii) statistical methods to capture associations. In this study, we used a panel of 314 maize inbred lines from the dent pool, composed of inbred material from public institutes (113 inbred lines) and a private company (201 inbred lines). We showed that local LD was higher and genetic diversity lower in the material of private origin than in the public material. We compared the results obtained by different software for identifying population structure and computing relatedness among lines, and ran association tests for earliness related traits. Our results confirmed the importance of the mite polymorphism of Vgt1 on flowering time, but also showed that its effect can be captured by zmRap2.7 polymorphisms located 70 kb apart. We also highlighted associations with polymorphisms within genes putatively involved in lignin biosynthesis pathway, which deserve further investigations.

The genetic basis of heterosis: multiparental quantitative trait loci mapping reveals contrasted levels of apparent overdominance among traits of agronomical interest in maize (Zea mays L.).

Understanding the genetic bases underlying heterosis is a major issue in maize (Zea mays L.). We extended the North Carolina design III (NCIII) by using three populations of recombinant inbred lines derived from three parental lines belonging to different heterotic pools, crossed with each parental line to obtain nine families of hybrids. A total of 1253 hybrids were evaluated for grain moisture, silking date, plant height, and grain yield. Quantitative trait loci (QTL) mapping was carried out on the six families obtained from crosses to parental lines following the "classical" NCIII method and with a multiparental connected model on the global design, adding the three families obtained from crosses to the nonparental line. Results of the QTL detection highlighted that most of the QTL detected for grain yield displayed apparent overdominance effects and limited differences between heterozygous genotypes, whereas for grain moisture predominance of additive effects was observed. For plant height and silking date results were intermediate. Except for grain yield, most of the QTL identified showed significant additive-by-additive epistatic interactions. High correlation observed between heterosis and the heterozygosity of hybrids at markers confirms the complex genetic basis and the role of dominance in heterosis. An important proportion of QTL detected were located close to the centromeres. We hypothesized that the lower recombination in these regions favors the detection of (i) linked QTL in repulsion phase, leading to apparent overdominance for heterotic traits and (ii) linked QTL in coupling phase, reinforcing apparent additive effects of linked QTL for the other traits.

Meta-analysis of QTL involved in silage quality of maize and comparison with the position of candidate genes.

A meta-analysis of quantitative trait loci (QTL) associated with plant digestibility and cell wall composition in maize was carried out using results from 11 different mapping experiments. Statistical methods implemented in "MetaQTL" software were used to build a consensus map, project QTL positions and perform meta-analysis. Fifty-nine QTL for traits associated with digestibility and 150 QTL for traits associated with cell wall composition were included in the analysis. We identified 26 and 42 metaQTL for digestibility and cell wall composition traits, respectively. Fifteen metaQTL with confidence interval (CI) smaller than 10 cM were identified. As expected from trait correlations, 42% of metaQTL for digestibility displayed overlapping CIs with metaQTL for cell wall composition traits. Coincidences were particularly strong on chromosomes 1 and 3. In a second step, 356 genes selected from the MAIZEWALL database as candidates for the cell wall biosynthesis pathway were positioned on our consensus map. Colocalizations between candidate genes and metaQTL positions appeared globally significant based on χ(2) tests. This study contributed in identifying key chromosomal regions involved in silage quality and potentially associated genes for most of these regions. These genes deserve further investigation, in particular through association mapping.

Detection of marker-QTL associations by studying change in marker frequencies with selection.

The value of selective genotyping for the detection of QTL has already been studied from a theoretical point of view but with the assumption of a negligible contribution (r2P) of the QTL to the phenotypic variance. For predicting change in gene frequency, we show that this assumption is only valid for r2P less than 0.05 and for a proportion selected higher than 1%. Therefore, we develop a study of the optimization of selective genotyping without assumption on QTL effect, with selection either of both tails (bidirectional genotyping or BSG) or only one tail (unidirectional genotyping or USG). For a given population size of phenotyped plants the optimal proportion selected for selective genotyping is around 30% for each tail. For the same investment as in ANOVA, by investing more in phenotyping than in genotyping when the cost ratio of genotyping to phenotyping is higher than 1, the optimal proportion selected appears to be between 10 and 20% for each tail. It is mainly affected by the cost ratio and decreases when the cost ratio increases. At this optimum, BSG is competitive with ANOVA, or even more powerful, when the cost ratio is higher than 1. USG can also be competitive when the cost ratio is higher than 2. Using experimental data from two populations of about 300 F4 inbred families of maize, it was verified that BSG at the optimum gives the same results as ANOVA or is better whereas USG is less powerful or equivalent.

Connected populations for detecting quantitative trait loci and testing for epistasis: an application in maize.

Quantitative trait loci (QTL) detection experiments have often been restricted to large biallelic populations. Use of connected multiparental crosses has been proposed to increase the genetic variability addressed and to test for epistatic interactions between QTL and the genetic background. We present here the results of a QTL detection performed on six connected F(2) populations of 150 F(2:3) families each, derived from four maize inbreds and evaluated for three traits of agronomic interest. The QTL detection was carried out by composite interval mapping on each population separately, then on the global design either by taking into account the connections between populations or not. Epistatic interactions between loci and with the genetic background were tested. Taking into account the connections between populations increased the number of QTL detected and the accuracy of QTL position estimates. We detected many epistatic interactions, particularly for grain yield QTL (R(2) increase of 9.6%). Use of connections for the QTL detection also allowed a global ranking of alleles at each QTL. Allelic relationships and epistasis both contribute to the lack of consistency for QTL positions observed among populations, in addition to the limited power of the tests. The potential benefit of assembling favorable alleles by marker-assisted selection are discussed.

Maize introduction into Europe: the history reviewed in the light of molecular data.

The resolution that can be obtained from molecular genetic markers affords new prospects for understanding the dispersion of agricultural species from their primary origin centres. In order to study the introduction and the dispersion of maize in Europe, we have characterised a large and representative set of maize populations of both American and European origins for their variation at 29 restriction fragment length polymorphism loci. Polymorphism was higher for American populations than for European populations (respectively, 12.3 and 9.6 alleles per locus, on average), and only a few alleles were specific to European populations. Investigation of genetic similarity between populations from both continents made it possible to identify various types of American maize introduced into Europe at different times or in different places and which have given rise to distinctive European races. Beyond confirming the importance of Caribbean germplasm, the first maize type to be introduced into Europe, this research revealed that introductions of Northern American flint populations have played a key role in the adaptation of maize to the European climate. According to a detailed historical investigation, the introduction of these populations must have occurred shortly after the discovery of the New World.

RFLP diversity and relationships among traditional European maize populations.

Given the large extent of hybrid cultivation, the importance of conserving the diversity of crop genetic resources has given birth to numerous collections of old races. In the present paper, we conduct a molecular characterisation of a large collection of 488 European maize populations using the bulk RFLP analysis. The analysis of 23 RFLP loci showed a high allelic richness of 11.5 alleles per locus. Populations from eastern Europe (Poland, Austria, Germany, etc.) showed the lowest genetic diversity, a lower number of unique alleles and a higher percentage of fixed loci than populations from southern Europe. In fact, genetic diversity appeared higher in Southern regions where the first maize populations are thought to have been introduced. Molecular classification based on Rogers' distance (i.e. alleles frequencies) allowed us to distinguish three main clusters which were highly consistent with geographic origins. A Northeastern cluster grouped together early or intermediate populations from Northeastern countries and the Balkans, a southeastern cluster joined late and partially dent populations from Greece and Italy, and, a southwestern cluster was made up of early flint populations from northern Spain, Portugal and the Pyrenees. A correlation between allelic frequencies at some loci and latitude and/or longitude was observed. Such tendencies may reflect the direction of gene flow between different races of maize: for instance, North American (Northern flint) and Caribbean populations were introduced, respectively, to northern and southern Europe, in the past.

Large scale molecular analysis of traditional European maize populations. Relationships with morphological variation.

A representative sample of 130 European traditional maize populations was analysed for both their morphological and molecular variation. The morphological analysis of 19 variables revealed a significant variability. Correlation analysis allowed us to distinguish between traits affected by earliness (plant and ear height) and structural traits (plant architecture, grain structure). Two main morphological types could be distinguished. Molecular analyses were performed for 29 RFLP loci on DNA bulks. The number of alleles detected was high when compared to previous studies (9.59 alleles per locus). Genetic diversity was also high (0.55), with a strong differentiation between populations (GST value of 35.6%). A clear relationship between the genetic diversity of the populations and their agronomic performances was highlighted. Morphological and molecular distances showed a tendency towards a triangular relationship. We therefore considered a two-phase process to be the most efficient approach for the classification of genetic resources: firstly, a molecular study to define groups of genetically close populations, and secondly a morphological description of populations from each group. In our European collection, this approach allowed us to separate the populations from Northern and Southern Europe and to define six groups of genetically close populations, comparable to European races. This study opens new prospects concerning the molecular analysis of very large collections of genetic resources, hitherto limited by the necessity of individual analyses, and proposes a first molecular classification of European maize germplasm.

Relationships among maize inbred lines and populations from European and North-American origins as estimated using RFLP markers.

RFLP markers have proven to be a reliable and highly informative tool for characterizing genetic diversity in maize. Joint analysis of inbred lines and populations should provide valuable information with respect to (1) a better understanding of the genetic basis of present elite germplasm and (2) the identification of populations that may prove to be useful sources of genetic diversity for breeding programs. Sixty-two inbred lines of known heterotic groups and ten maize populations, some of them significant contributors to the genetic basis of the heterotic groups, were assayed at 28 RFLP loci. Joint data analyses first underlined that the populations displayed a large number of alleles that were absent in the set of inbred lines. Associations among inbreds and populations further proved consistent with pedigree data of the inbreds and provided new information on the genetical basis of heterotic groups. In particular, European flint inbreds were revealed to be as close to the Northeastern U.S. flint population studied as to the typical European populations. These results advocate the analysis of larger sets of populations by means of molecular markers in order to (1) gain insight into the history of maize germplasm and (2) set up appropriate strategies for the use of genetic resources in breeding programs.

Marker-assisted selection efficiency in populations of finite size.

The efficiency of marker-assisted selection (MAS) based on an index incorporating both phenotypic and molecular information is evaluated with an analytical approach that takes into account the size of the experiment. We consider the case of a population derived from a cross between two homozygous lines, which is commonly used in plant breeding, and we study the relative efficiency of MAS compared with selection based only on phenotype in the first cycle of selection. It is shown that the selection of the markers included in the index leads to an overestimation of the effects associated with these markers. Taking this bias into account, we study the influence of several parameters, including experiment size and heritability, on MAS efficiency. Even if MAS appears to be most interesting for low heritabilities, we point out the existence of an optimal heritability (approximately 0.2) below which the low power of quantitative trait loci detection and the bias caused by the selection of markers reduce the efficiency. In this situation, increasing the power of detection by using a higher probability of type I error can improve MAS efficiency. This approach, validated by simulations, gives results that are generally consistent with those previously obtained by simulations using a more sophisticated biological model than ours. Thus, though developed from a simple genetic model, our approach may be a useful tool to optimize the experimental means for more complex genetic situations.

Marker-assisted introgression of quantitative trait loci.

The use of molecular markers for the introgression of one or several superior QTL alleles into a recipient line is investigated using analytic and simulation results. The positions of the markers devoted to the control of the genotype at the QTLs in a "foreground selection" step are optimized given the confidence interval of the QTL position. Results demonstrate that using at least three markers per QTL allows a good control over several generations. Population sizes that should be recommended for various numbers of QTLs are calculated and are used to determine the limit in the number of QTLs that can be monitored simultaneously. If "background selection" devoted to accelerate the return to the recipient parent genotype outside the QTL regions is applied, the positions of the markers devoted to the control of the QTLs have to be reconsidered. When several QTLs are monitored simultaneously, background selection among the limited number of individuals resulting from the foreground selection step accelerates the increase in genomic similarity with the recipient parent, with only limited costs. Background selection is even more efficient in a pyramidal backcross program where QTLs are first monitored one by one.