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Cold reduces maize (Zea mays L.) production and delays sowings. Cold tolerance in maize is very limited, and breeding maize for cold tolerance is still a major challenge. Our objective was to detect QTL for cold tolerance at germination and seedling stages. We evaluated, under cold and control conditions, 919 Dent and 1009 Flint inbred lines from two nested association mapping designs consisting in 24 double-haploid populations, genotyped with 56,110 SNPs. We found a large diversity of maize cold tolerance within these NAM populations. We detected one QTL for plant weight and four for fluorescence under cold conditions, as well as one for plant weight and two for chlorophyll content under control conditions in the Dent-NAM. There were fewer significant QTL under control conditions than under cold conditions, and half of the QTL were for quantum efficiency of photosystem II. Our results supported the large genetic discrepancy between optimal and low temperatures, as the quantity and the position of the QTL were very variable between control and cold conditions. Furthermore, as we have not found alleles with significant effects on these NAM designs, further studies are needed with other experimental designs to find favorable alleles with important effects for improving cold tolerance in maize. [ABSTRACT FROM AUTHOR]

Key message: Model training on data from all selection cycles yielded the highest prediction accuracy by attenuating specific effects of individual cycles. Expected reliability was a robust predictor of accuracies obtained with different calibration sets. The transition from phenotypic to genome-based selection requires a profound understanding of factors that determine genomic prediction accuracy. We analysed experimental data from a commercial maize breeding programme to investigate if genomic measures can assist in identifying optimal calibration sets for model training. The data set consisted of six contiguous selection cycles comprising testcrosses of 5968 doubled haploid lines genotyped with a minimum of 12,000 SNP markers. We evaluated genomic prediction accuracies in two independent prediction sets in combination with calibration sets differing in sample size and genomic measures (effective sample size, average maximum kinship, expected reliability, number of common polymorphic SNPs and linkage phase similarity). Our results indicate that across selection cycles prediction accuracies were as high as 0.57 for grain dry matter yield and 0.76 for grain dry matter content. Including data from all selection cycles in model training yielded the best results because interactions between calibration and prediction sets as well as the effects of different testers and specific years were attenuated. Among genomic measures, the expected reliability of genomic breeding values was the best predictor of empirical accuracies obtained with different calibration sets. For grain yield, a large difference between expected and empirical reliability was observed in one prediction set. We propose to use this difference as guidance for determining the weight phenotypic data of a given selection cycle should receive in model retraining and for selection when both genomic breeding values and phenotypes are available. [ABSTRACT FROM AUTHOR]

Key message: High genetic variation in two European maize landraces can be harnessed to improve Gibberella ear rot resistance by integrated genomic tools. Fusarium graminearum (Fg) causes Gibberella ear rot (GER) in maize leading to yield reduction and contamination of grains with several mycotoxins. This study aimed to elucidate the molecular basis of GER resistance among 500 doubled haploid lines derived from two European maize landraces, "Kemater Landmais Gelb" (KE) and "Petkuser Ferdinand Rot" (PE). The two landraces were analyzed individually using genome-wide association studies and genomic selection (GS). The lines were genotyped with a 600-k maize array and phenotyped for GER severity, days to silking, plant height, and seed-set in four environments using artificial infection with a highly aggressive Fg isolate. High genotypic variances and broad-sense heritabilities were found for all traits. Genotype-environment interaction was important throughout. The phenotypic (r) and genotypic ( r g ) correlations between GER severity and three agronomic traits were low (r = − 0.27 to 0.20; r g = − 0.32 to 0.22). For GER severity, eight QTLs were detected in KE jointly explaining 34% of the genetic variance. In PE, no significant QTLs for GER severity were detected. No common QTLs were found between GER severity and the three agronomic traits. The mean prediction accuracies (ρ ) of weighted GS (wRR-BLUP) were higher than ρ of marker-assisted selection (MAS) and unweighted GS (RR-BLUP) for GER severity. Using KE as the training set and PE as the validation set resulted in very low ρ that could be improved by using fixed marker effects in the GS model. [ABSTRACT FROM AUTHOR]

Key Message: Increased efficiencies achieved in different steps of DH line production offer greater benefits to maize breeding programs. Doubled haploid (DH) technology has become an integral part of many commercial maize breeding programs as DH lines offer several economic, logistic and genetic benefits over conventional inbred lines. Further, new advances in DH technology continue to improve the efficiency of DH line development and fuel its increased adoption in breeding programs worldwide. The established method for maize DH production covered in this review involves in vivo induction of maternal haploids by a male haploid inducer genotype, identification of haploids from diploids at the seed or seedling stage, chromosome doubling of haploid (D0) seedlings and finally, selfing of fertile D0 plants. Development of haploid inducers with high haploid induction rates and adaptation to different target environments have facilitated increased adoption of DH technology in the tropics. New marker systems for haploid identification, such as the red root marker and high oil marker, are being increasingly integrated into new haploid inducers and have the potential to make DH technology accessible in germplasm such as some Flint, landrace, or tropical material, where the standard R1-nj marker is inhibited. Automation holds great promise to further reduce the cost and time in haploid identification. Increasing success rates in chromosome doubling protocols and/or reducing environmental and human toxicity of chromosome doubling protocols, including research on genetic improvement in spontaneous chromosome doubling, have the potential to greatly reduce the production costs per DH line. [ABSTRACT FROM AUTHOR]

Key message: Mainly additive gene action governed inheritance of haploid male fertility, although epistatic effects were also significant. Recurrent selection for haploid male fertility resulted in substantial improvement in this trait. The doubled haploid (DH) technology offers several advantages in maize breeding compared to the traditional method of recurrent selfing. However, there is still great potential for improving the success rate of DH production. Currently, the majority of haploid plants are infertile after chromosome doubling treatment by antimitotic agents such as colchicine and cannot be selfed for production of DH lines. Improvement in haploid male fertility (HMF) by selection for a higher spontaneous chromosome doubling rate (SDR) has the potential to increase DH production efficiency. To investigate the gene action governing SDR in two breeding populations, we adapted the quantitative-genetic model of Eberhart and Gardner (in Biometrics 22:864–881. 10.2307/2528079, 1966) for the case of haploid progeny from ten DH lines and corresponding diallel crosses. Furthermore, we carried out three cycles of recurrent selection for SDR in two additional populations to evaluate the selection gain for this trait. Additive genetic effects predominated in both diallel crosses, but epistatic effects were also significant. Entry-mean heritability of SDR observed for haploid progeny of these populations exceeded 0.91, but the single-plant heritability relevant to selection was low, ranging from 0.11 to 0.19. Recurrent selection increased SDR from approximately 5–50%, which suggests the presence of few QTL with large effects. This improvement in HMF is greater than the effect of standard colchicine treatment, which yields at maximum 30% fertile haploids. Altogether, the results show the great potential of spontaneous chromosome doubling to streamline development DH lines and to enable new breeding schemes with more efficient allocation of resources. [ABSTRACT FROM AUTHOR]

Key message: Selected doubled haploid lines averaged similar testcross performance as their original landraces, and the best of them approached the yields of elite inbreds, demonstrating their potential to broaden the narrow genetic diversity of the flint germplasm pool. Maize landraces represent a rich source of genetic diversity that remains largely idle because the high genetic load and performance gap to elite germplasm hamper their use in modern breeding programs. Production of doubled haploid (DH) lines can mitigate problems associated with the use of landraces in pre-breeding. Our objective was to assess in comparison with modern materials the testcross performance (TP) of the best 89 out of 389 DH lines developed from six landraces and evaluated in previous studies for line per se performance (LP). TP with a dent tester was evaluated for the six original landraces, ~ 15 DH lines from each landrace selected for LP, and six elite flint inbreds together with nine commercial hybrids for grain and silage traits. Mean TP of the DH lines rarely differed significantly from TP of their corresponding landrace, which averaged in comparison with the mean TP of the elite flint inbreds ~ 20% lower grain yield and ~ 10% lower dry matter and methane yield. Trait correlations of DH lines closely agreed with the literature; correlation of TP with LP was zero for grain yield, underpinning the need to evaluate TP in addition to LP. For all traits, we observed substantial variation for TP among the DH lines and the best showed similar TP yields as the elite inbreds. Our results demonstrate the high potential of landraces for broadening the narrow genetic base of the flint heterotic pool and the usefulness of the DH technology for exploiting idle genetic resources from gene banks. [ABSTRACT FROM AUTHOR]

Key message: Inclusion of historical training data improved the genomics-based prediction of performance of maize hybrids, the extent depending on the phenotypic trait and genotype-by-year interaction. Prediction of hybrid performance using existing phenotypic data on previous hybrids combined with molecular data collected on the parent lines allows to identify the most promising candidates from a huge number of possible hybrids at an early stage. Phenotypic data on yield and dry matter of 1970 grain maize hybrids from 19 years of a public breeding program were aggregated considering the underlying structure of factorial sets of hybrids. Pedigree records and 50 K SNP data were collected on their 170 Dent and 127 Flint parent lines. The performance of untested hybrids was predicted by best linear unbiased predictors (BLUP) on basis of pedigree or genomic data. For composition of training sets (TRN) and test sets (TST), three schemes for collecting factorials from specific years were employed which resulted in 490 scenarios. For each scenario, the predictive ability and genomic relationship between TRN and TST hybrids were determined. For extended TRNs, where earlier years were successively added to the TRN, the maximum relationship increased and the predictive ability improved, with the extent of the latter depending on the phenotypic trait and its genotype-by-year interaction. Genomic BLUP outperformed pedigree BLUP and better utilized the early years' data, especially for prediction of hybrids from factorials in a more distant future. This study on hybrid prediction in grain maize illustrated that including historical phenotypic data for training, although consisting of less related genotypes, can improve genomic prediction and enables optimization of hybrid variety development. [ABSTRACT FROM AUTHOR]

Background: Small RNA (sRNA) sequences are known to have a broad impact on gene regulation by various mechanisms. Their performance for the prediction of hybrid traits has not yet been analyzed. Our objective was to analyze the relation of parental sRNA expression with the performance of their hybrids, to develop a sRNA-based prediction approach, and to compare it to more common SNP and mRNA transcript based predictions using a factorial mating scheme of a maize hybrid breeding program. Results: Correlation of genomic differences and messenger RNA (mRNA) or sRNA expression differences between parental lines with hybrid performance of their hybrids revealed that sRNAs showed an inverse relationship in contrast to the other two data types. We associated differences for SNPs, mRNA and sRNA expression between parental inbred lines with the performance of their hybrid combinations and developed two prediction approaches using distance measures based on associated markers. Cross-validations revealed parental differences in sRNA expression to be strong predictors for hybrid performance for grain yield in maize, comparable to genomic and mRNA data. The integration of both positively and negatively associated markers in the prediction approaches enhanced the prediction accurary. The associated sRNAs belong predominantly to the canonical size classes of 22- and 24-nt that show specific genomic mapping characteristics. Conclusion: Expression profiles of sRNA are a promising alternative to SNPs or mRNA expression profiles for hybrid prediction, especially for plant species without reference genome or transcriptome information. The characteristics of the sRNAs we identified suggest that association studies based on breeding populations facilitate the identification of sRNAs involved in hybrid performance. [ABSTRACT FROM AUTHOR]

Sorting and selection of individual seeds by their oil content (OC) or oil mass from larger quantities of seeds is an important step for many applications in the breeding of oil seed crops. Time-domain nuclear magnetic resonance (NMR) has proved to be a very precise method for non-destructive OC measurement of seeds; however, benchtop NMR devices are not automated for high throughput. Our objectives were to construct a high-throughput platform for (i) singling seeds from bulks, (ii) measurement of their mass, (iii) measurement of their oil mass with NMR, and (iv) either sorting the measured seeds into fractions on the basis of their OC or placement of seeds individually in matrix trays for subsequent selection based on the recorded seed data. Modules for each of these tasks, some newly developed, were linked in a novel approach by transporting single seeds between modules using a combination of pneumatic and mechanical elements, as well as software for control of the platforms' parts and for remote control. Our platform enables fully automated measurement of up to 600 seeds h −1 . Maize seeds were used to demonstrate the applicability of our platform for measurements of OC and seed mass. For both traits, repeatability and accuracy were extraordinarily high. The platform proved robust and stable in long series of measurements and represents a break-through for OC determination in the breeding of maize and oil seed crops. [ABSTRACT FROM AUTHOR]

mRNA transcription profiles are an alternative to DNA markers for predicting hybrid performance. Our objective was to investigate their prediction accuracy in an unbalanced maize data set. We focused on the effectiveness of preselecting a core set of genes for transcription profiling and on the comparison of prediction models. A total of 254 hybrids were evaluated for grain yield and grain dry matter content. The mRNA transcripts of a core set of 2k genes and the genotype of 1k AFLP markers were assessed in the parental lines. Predictions based on transcriptome-based distances determined from the 2k core set of genes resulted in prediction accuracies below 0.5 and could not reach the high accuracies observed with a 46k micro-array in earlier studies. Predictions based on ridge regression resulted in prediction accuracies greater 0.6. Only marginal differences were observed in the prediction accuracies of mRNA transcripts compared with AFLPs. We conclude that mRNA transcription profiles are suitable for hybrid prediction with ridge-regression models in unbalanced designs, even if limited resources allow only transcription profiling of a core set of genes. [ABSTRACT FROM AUTHOR]

mRNA transcription profiles has not yet been investigated. Our objective was to compare the prediction accuracy of models employing mRNA transcription profiles with that of models employing genome-wide markers using a data set of 98 maize hybrids from a breeding program. Results: We predicted hybrid performance and mid-parent heterosis for grain yield and grain dry matter content and employed cross validation to assess the prediction accuracy. Prediction with a ridge regression model using random effects for mRNA transcription profiles resulted in similar prediction accuracies than employing the model to DNA markers. For hybrids, of which none of the parental inbred lines was part of the training set, the ridge regression model did not reach the prediction accuracy that was obtained with a model using transcriptome-based distances. Conclusion: We conclude that mRNA transcription profiles are a promising alternative to DNA markers for hybrid prediction, but further studies with larger data sets are required to investigate the superiority of alternative prediction models. [ABSTRACT FROM AUTHOR]

Rapid production of inbred lines by in vivo haploid induction has become a routine method in maize breeding. Limitations of the present method can be overcome by use of inducers with high seed-oil content for discrimination of haploid (H) from diploid crossing (C) seeds. With regard to the optimum application of this new approach, our goal was to find the most accurate discrimination method comparing the directly measured parameters oil mass (OM) and seed weight (SW) with the derived parameter oil content (OC). For this, we compared the distribution properties of H and C seeds from 11 induction crosses with high-oil inducers for all three traits. The distributions of H and C seeds overlapped almost completely for SW but overlapped less for OC than for OM owing to a much smaller coefficient of variation in both fractions. Thus, the false discovery rate and false negative rate for sorting of H and C seeds were generally smaller for OC than for OM. The optimal bivariate discrimination function on the basis of OM and SW yielded similar error rates as a univariate discrimination function on the basis of OC alone. In conclusion, we recommend to measure seeds from induction crosses produced with high-oil inducers for SW in addition to OM and use OC as a simple and robust criterion for sorting of H and C seeds. [ABSTRACT FROM AUTHOR]

Maize (Zea mays L.) for northern growing areas requires cold tolerance for extending the vegetative period. Our objectives were to evaluate two large panels of maize inbred lines adapted to Europe for cold tolerance and to estimate the effects of cold-related traits on biomass production. Two inbred panels were evaluated for cold tolerance per se and in testcrosses under cold and control conditions in a growth chamber and under field conditions. Comparisons of inbreds and groups of inbreds were made taking into account the single nucleotide polymorphisms (SNP)-based genetic structure of the panels, and the factors affecting biomass production were studied. Eight flint and one dent inbred with diverse origins were the most cold tolerant. The most cold-tolerant dent and flint groups were the Iodent Ph207 and the Northern Flint D171 groups, respectively. The relationships between inbred per se and testcross performance and between controlled and field conditions were low. Regressions with dry matter yield in the field as dependent variable identified plant height (R² = 0.285) as the main independent variable, followed by quantum efficiency of photosystem II (R² = 0.034) and other traits with minor contributions. Cold-tolerance- related traits had low and negative effects on dry matter yield. Models intending the prediction of final performance from traits scored in early developmental stages are not expected to be precise enough for breeding. For improving cold tolerance, inbreds released from crosses among the No Iodent group and the Northern Flint group may show high combining ability, as well as between both groups and the Northern Flint D171 group. [ABSTRACT FROM AUTHOR]

Chilling sensitivity of maize is a strong limitation for its cultivation in the cooler areas of the northern and southern hemisphere because reduced growth in early stages impairs on later biomass accumulation. Efficient breeding for chilling tolerance is hampered by both the complex physiological response of maize to chilling temperatures and the difficulty to accurately measure chilling tolerance in the field under fluctuating climatic conditions. For this research, we used genome-wide association ( GWA) mapping to identify genes underlying chilling tolerance under both controlled and field conditions in a broad germplasm collection of 375 maize inbred lines genotyped with 56 110 single nucleotide polymorphism (SNP). We identified 19 highly significant association signals explaining between 5.7 and 52.5% of the phenotypic variance observed for early growth and chlorophyll fluorescence parameters. The allelic effect of several SNPs identified for early growth was associated with temperature and incident radiation. Candidate genes involved in ethylene signalling, brassinolide, and lignin biosynthesis were found in their vicinity. The frequent involvement of candidate genes into signalling or gene expression regulation underlines the complex response of photosynthetic performance and early growth to climatic conditions, and supports pleiotropism as a major cause of co-locations of quantitative trait loci for these highly polygenic traits. [ABSTRACT FROM AUTHOR]

To optimize the efficiency of maize (Zea mays L.) drought breeding, the ability to predict testcross performance (TP) under drought stress using line per se performance (LP) of the parental inbreds would be useful. We evaluated LP and TP of tropical inbreds in well-watered and drought environments in Kenya and Mexico. Our main objective was to determine if LP under drought stress was predictive of TP for grain yield under drought stress and if selection for LP under drought stress would result in reduced yield potential for TP under well-watered conditions. Average yield reduction under drought stress was 77% for lines and 68% for testcrosses. Average genotypic correlations between lines and testcrosses under drought stress were positive and low (genotypic correlation = 0.48), but correlations increased with increasing levels of drought stress in both LP and TP trials. Averaged over all sets, indirect selection for LP was predicted to be only 57% as effective as direct selection for TP under drought stress but was on average substantially higher in testcross sets where yield reduction due to drought was 70% or more. Therefore, LP under drought stress could be used to develop hybrids for severely drought-prone environments. Moreover, LP under drought stress was uncorrelated with TP for grain yield under well-watered conditions, showing that selection of lines per se for drought tolerance would likely not reduce yield potential of testcrosses. [ABSTRACT FROM AUTHOR]

The exchange of elite breeding materials across regions is an important way in which multinational maize breeding programmes access new genetic variation, improve efficiency and reduce costs. Our objectives were to examine whether CIMMYT's breeding programmes for tropical and subtropical environments in Mexico and Eastern and Southern Africa ( ESA) can effectively share materials. Sets of selected and unselected lines were evaluated for per se and testcross performance in multiple environments in Mexico and ESA for grain yield, days to anthesis and plant height. Genotypic correlations between performance in Mexico and ESA as testcross and line per se were high (≥ 0.72) for all experiments, and indirect selection efficiency ranged from 67 to over 100% for all traits. Lines selected in ESA or Latin America performed equally well in each region, indicating selection was for broad rather than regional adaptation. Thus, breeding programmes of CIMMYT in both Mexico and ESA can benefit tremendously by exchanging breeding materials and test results, and elite selections from each region should be fast-tracked for evaluation in the other. [ABSTRACT FROM AUTHOR]

Landraces are valuable genetic resources for broadening the genetic base of elite germplasm in maize. Extensive exploitation of landraces has been hampered by their genetic heterogeneity and heavy genetic load. These limitations may be overcome by the in-vivo doubled haploid (DH) technique. A set of 132 DH lines derived from three European landraces and 106 elite flint (EF) lines were genotyped for 56,110 single nucleotide polymorphism (SNP) markers and evaluated in field trials at five locations in Germany in 2010 for several agronomic traits. In addition, the landraces were compared with synthetic populations produced by intermating DH lines derived from the respective landrace. Our objectives were to (1) evaluate the phenotypic and molecular diversity captured within DH lines derived from European landraces, (2) assess the breeding potential (usefulness) of DH lines derived from landraces to broaden the genetic base of the EF germplasm, and (3) compare the performance of each landrace with the synthetic population produced from the respective DH lines. Large genotypic variances among DH lines derived from landraces allowed the identification of DH lines with grain yields comparable to those of EF lines. Selected DH lines may thus be introgressed into elite germplasm without impairing its yield level. Large genetic distances of the DH lines to the EF lines demonstrated the potential of DH lines derived from landraces to broaden the genetic base of the EF germplasm. The comparison of landraces with their respective synthetic population showed no yield improvement and no reduction of phenotypic diversity. Owing to the low population structure and rapid decrease of linkage disequilibrium within populations of DH lines derived from landraces, these would be an ideal tool for association mapping. Altogether, the DH technology opens new opportunities for characterizing and utilizing the genetic diversity present in gene bank accessions of maize. [ABSTRACT FROM AUTHOR]

With 1 figure and 2 tables Abstract Gibberella ear rot (GER) of maize caused by Fusarium graminearum leads to contamination of grains with mycotoxins such as deoxynivalenol (DON), thus reducing the quality of food and feed. A generation means analysis was conducted to estimate gene effects influencing the resistance to GER and DON contamination in flint maize germplasm adapted to Central Europe. Five crosses of two resistant and two susceptible flint inbred lines were developed, and each cross comprised both parent lines (P1, P2) as well as the F1 and F2 generation and the first backcross to both parents (BC1-P1, BC1-P2). All entries were grown in four environments and artificially inoculated with F. graminearum. There was a prevalence of additive gene action, while significant dominance effects were found in only one cross for resistance to GER, but in four crosses for resistance to DON contamination. Owing to the prevalence of additive gene action, the prospects are good to improve the resistance of the flint germplasm and to accumulate more favourable gene combinations in future breeding lines. [ABSTRACT FROM AUTHOR]

Information about the genetic diversity and population structure in elite breeding material is of fundamental importance for the improvement of crops. The objectives of our study were to (a) examine the population structure and the genetic diversity in elite maize germplasm based on simple sequence repeat (SSR) markers, (b) compare these results with those obtained from single nucleotide polymorphism (SNP) markers, and (c) compare the coancestry coefficient calculated from pedigree records with genetic distance estimates calculated from SSR and SNP markers. Our study was based on 1,537 elite maize inbred lines genotyped with 359 SSR and 8,244 SNP markers. The average number of alleles per locus, of group specific alleles, and the gene diversity ( D) were higher for SSRs than for SNPs. Modified Roger’s distance (MRD) estimates and membership probabilities of the STRUCTURE matrices were higher for SSR than for SNP markers but the germplasm organization in four heterotic pools was consistent with STRUCTURE results based on SSRs and SNPs. MRD estimates calculated for the two marker systems were highly correlated (0.87). Our results suggested that the same conclusions regarding the structure and the diversity of heterotic pools could be drawn from both markers types. Furthermore, although our results suggested that the ratio of the number of SSRs and SNPs required to obtain MRD or D estimates with similar precision is not constant across the various precision levels, we propose that between 7 and 11 times more SNPs than SSRs should be used for analyzing population structure and genetic diversity. [ABSTRACT FROM AUTHOR]

In hybrid maize ( Zea mays L.) breeding, doubled haploids (DH) are increasingly replacing inbreds developed by recurrent selfing. Doubled haploids may be developed directly from S0 plants in the parental cross or via S1 families. In both these breeding schemes, we examined 2 two-stage selecting strategies, i.e., considering or ignoring cross and family structure while selection among and within parental crosses and S1 families. We examined the optimum allocation of resources to maximize the selection gain Δ G and the probability P( q) of identifying the q% best genotypes. Our specific objectives were to (1) determine the optimum number and size of crosses and S1 families, as well as the optimum number of test environments and (2) identify the superior selection strategy. Selection was based on the evaluation of testcross progenies of (1) DH lines in both stages (DHTC) and (2) S1 families in the first stage and of DH lines within S1 families in the second stage (S1TC-DHTC) with uniform and variable sizes of crosses and S1 families. We developed and employed simulation programs for selection with variable sizes of crosses and S1 families within crosses. The breeding schemes and selection strategies showed similar relative efficiency for both optimization criteria Δ G and P (0.1%). As compared with DHTC, S1TC-DHTC had larger Δ G and P (0.1%), but a higher standard deviation of Δ G. The superiority of S1TC-DHTC was increased when the selection was done among all DH lines ignoring their cross and family structure and using variable sizes of crosses and S1 families. In DHTC, the best selection strategy was to ignore cross structures and use uniform size of crosses. [ABSTRACT FROM AUTHOR]

Maize ( Zea mays L.) breeders are concerned about the narrowing of the genetic base of elite germplasm. To reverse this trend, elite germplasm from other geographic regions can be introgressed, but due to lack of adaptation it is difficult to assess their breeding potential in the targeted environment. The objectives of this study were to (1) investigate the relationship between European and US maize germplasm, (2) examine the suitability of different mega-environments and measures of performance to assess the breeding potential of exotics, and (3) study the relationship of genetic distance with mid-parent heterosis (MPH). Eight European inbreds from the Dent and Flint heterotic groups, 11 US inbreds belonging to Stiff Stalk (SS), non-Stiff Stalk (NSS), and CIMMYT Pool 41, and their 88 factorial crosses in F1 and F2 generations were evaluated for grain yield and dry matter concentration. The experiments were conducted in three mega-environments: Central Europe (target mega-environment), US Cornbelt (mega-environment where donor lines were developed), and Southeast Europe (an intermediate mega-environment). The inbreds were also fingerprinted with 266 SSR markers. Suitable criteria to identify promising exotic germplasm were F1 hybrid performance in the targeted mega-environment and F1 and parental performance in the intermediate mega-environment. Marker-based genetic distances reflected relatedness among the inbreds, but showed no association with MPH. Based on genetic distance, MPH, and F1 performance, we suggest to introgress SS germplasm into European Dents and NSS into European Flints, in order to exploit the specific adaptation of European flint germplasm and the excellent combining ability of US germplasm in European maize breeding programs. [ABSTRACT FROM AUTHOR]

The ratio of variance due to specific vs. general combining ability (GCA) (σ2SCA:σ2GCA) is of central importance for predicting hybrid performance from GCA effects. The objectives of our study were to (1) analyse the changes in estimates of σ2GCA, σ2SCA and their ratio during 30 years of hybrid maize breeding and (2) compare the observed trends in genetic variances with those expected under a simple genetic model. We analysed multilocation yield trials based on the North Carolina Design II conducted in the maize breeding programme of the University of Hohenheim from 1975 to 2004 for grain yield (GY) and dry matter content (DMC). GY showed a significant (P < 0.05) annual increase of 0.17 Mg/ha, but no linear trend was found for DMC. Since the beginning of hybrid breeding at the University of Hohenheim, the sum of estimates of σ2GCA of the flint and dent heterotic groups were higher than the estimates of their σ2SCA. This predominance did not change with ongoing inter-population improvement. Consequently, superior hybrids can be identified and selected mainly based on their prediction from GCA effects. [ABSTRACT FROM AUTHOR]

Parental selection influences the gain from selection and the optimum allocation of test resources in breeding programs. We compared two hybrid maize ( Zea mays L.) breeding schemes with evaluation of testcross progenies: (a) doubled haploid (DH) lines in both stages (DHTC) and (b) S1 families in the first stage and DH lines within S1 families in the second stage (S1TC-DHTC). Our objectives were to (1) determine the optimum allocation regarding the number of crosses, S1 families, DH lines, and test locations, (2) investigate the impact of parental selection on the optimum allocation and selection gain (Δ G), and (3) compare the maximum Δ G achievable with each breeding scheme. Selection gain was calculated by numerical integration. Different assumptions were made regarding the budget, variance components, correlation between the mean phenotypic performance of the parents and the mean genotypic value of the testcross performance of their progenies (ρ P ), and the composition of the finally selected test candidates. In comparison with randomly chosen crosses, maximum Δ G was largely increased with parental selection in both breeding schemes. With an increasing correlation ρ P , this superiority increased strongly, while the optimum number of crosses decreased in favor of an increased number of test candidates within crosses. Thus, concentration on few crosses among the best parental lines might be a promising approach for short-term success in advanced cycle breeding. Breeding scheme S1TC-DHTC led to a larger Δ G but had a longer cycle length than DHTC. However, with further improvements in the DH technique and the realization of more than two generations per year, early testing of S1 families prior to production of DH lines would become very attractive in hybrid maize breeding. [ABSTRACT FROM AUTHOR]

Early testing prior to doubled haploid (DH) production is a promising approach in hybrid maize breeding. We (1) determined the optimum allocation of the number of S1 families, DH lines, and test locations for two different breeding schemes, (2) compared the maximum selection gain achievable under both breeding schemes, and (3) investigated limitations in the current method of DH production. Selection gain was calculated by numerical integration in two-stage breeding schemes with evaluation of testcross progenies of (1) DH lines in both stages (DHTC), or (2) S1 families in the first and DH lines within S1 families in the second stage (S1TC-DHTC). Different assumptions were made regarding the budget, variance components, and time of DH production within S1 families. Maximum selection gain in S1TC-DHTC was about 10% larger than in DHTC, indicating the large potential of early testing prior to DH production. The optimum allocation of test resources in S1TC-DHTC involved similar numbers of test locations and test candidates in both stages resulting in a large optimum number of S1 families in the first stage and DH lines within the best two S1 families in the second stage. The longer cycle length of S1TC-DHTC can be compensated by haploid induction of individual S1 plants instead of S1 families. However, this reduces selection gain largely due to the current limitations in the DH technique. Substantial increases in haploid induction and chromosome doubling rates as well as reduction in costs of DH production would allow early testing of S1 lines and subsequent production and testing of DH lines in a breeding scheme that combines high selection gain with a short cycle length. [ABSTRACT FROM AUTHOR]

Association mapping holds great promise for the detection of quantitative trait loci (QTL) in plant breeding populations. The main objectives of this study were to (1) adapt the quantitative pedigree disequilibrium test to typical pedigrees of inbred lines produced in plant breeding programs, (2) compare the newly developed quantitative inbred pedigree disequilibrium test (QIPDT) with the commonly employed logistic regression ratio test (LRRT), with respect to the power and type I error rate of QTL detection, and (3) demonstrate the use of the QIPDT by applying it to flowering data of European elite maize inbreds. QIPDT and LRRT were compared based on computer simulations modeling 55 years of hybrid maize breeding in Central Europe. Furthermore, we applied QIPDT to a cross-section of 49 European elite maize inbred lines genotyped with 722 amplified fragment length polymorphism markers and phenotyped in four environments for days to anthesis. Compared to LRRT, the power to detect QTL was higher with QIPDT when using data collected routinely in plant breeding programs. Application of QIPDT to the 49 European maize inbreds resulted in a significant ( P < 0.05) association located at a position for which a consensus QTL was detected in a previous study. The results of our study suggested that QIPDT is a promising QTL detection method for data collected routinely in plant breeding programs. [ABSTRACT FROM AUTHOR]

Prediction methods to identify single-cross hybrids with superior yield performance have the potential to greatly improve the efficiency of commercial maize ( Zea mays L.) hybrid breeding programs. Our objectives were to (1) identify marker loci associated with quantitative trait loci for hybrid performance or specific combining ability (SCA) in maize, (2) compare hybrid performance prediction by genotypic value estimates with that based on general combining ability (GCA) estimates, and (3) investigate a newly proposed combination of the GCA model with SCA predictions from genotypic value estimates. A total of 270 hybrids was evaluated for grain yield and grain dry matter content in four Dent × Flint factorial mating experiments, their parental inbred lines were genotyped with 20 AFLP primer-enzyme combinations. Markers associated significantly with hybrid performance and SCA were identified, genotypic values and SCA effects were estimated, and four hybrid performance prediction approaches were evaluated. For grain yield, between 38 and 98 significant markers were identified for hybrid performance and between zero and five for SCA. Estimates of prediction efficiency ( R 2) ranged from 0.46 to 0.86 for grain yield and from 0.59 to 0.96 for grain dry matter content. Models enhancing the GCA approach with SCA estimates resulted in the highest prediction efficiency if the SCA to GCA ratio was high. We conclude that it is advantageous for prediction of single-cross hybrids to enhance a GCA-based model with SCA effects estimated from molecular marker data, if SCA variances are of similar or larger importance as GCA variances. [ABSTRACT FROM AUTHOR]

Four cycles of modified recurrent full-sib (FS) selection were conducted in an intermated F2 population of European flint maize. The objectives of our study were to monitor trends across selection cycles in the estimates of population mean, inbreeding coefficients and variance components, and to investigate the usefulness of best linear unbiased prediction (BLUP) of progeny performance under the recurrent FS selection scheme applied. We used a selection rate of 25% for a selection index, based on grain yield and dry matter content. A pseudo-factorial mating scheme was used for recombination. In this scheme, the selected FS families were divided into an upper-ranking group of parents mated to the lower-ranking group. Variance components were estimated with restricted maximum likelihood (REML). Average grain yield increased 1.2 t/ha per cycle, average grain moisture decreased 20.1 g/kg per cycle, and the selection index relative to the F2 check entries decreased 0.3% per cycle. For a more precise calculation of selection response, the four cycles should be tested together in multi-environmental trials. We observed a significant decrease in additive variance in the selection index, suggesting smaller future selection response. Predictions of FS family performance in Cn + 1 based on mean performance of parental FS families in Cn were of equal precision as those based on the mean additive genetic BLUP of their parents, and corresponding correlations were of moderate size for grain moisture and selection index. [ABSTRACT FROM AUTHOR]

Optimum allocation of resources is of fundamental importance for the efficiency of breeding programs. The objectives of our study were to (1) determine the optimum allocation for the number of lines and test locations in hybrid maize breeding with doubled haploids (DHs) regarding two optimization criteria, the selection gain Δ G k and the probability P k of identifying superior genotypes, (2) compare both optimization criteria including their standard deviations (SDs), and (3) investigate the influence of production costs of DHs on the optimum allocation. For different budgets, number of finally selected lines, ratios of variance components, and production costs of DHs, the optimum allocation of test resources under one- and two-stage selection for testcross performance with a given tester was determined by using Monte Carlo simulations. In one-stage selection, lines are tested in field trials in a single year. In two-stage selection, optimum allocation of resources involves evaluation of (1) a large number of lines in a small number of test locations in the first year and (2) a small number of the selected superior lines in a large number of test locations in the second year, thereby maximizing both optimization criteria. Furthermore, to have a realistic chance of identifying a superior genotype, the probability P k of identifying superior genotypes should be greater than 75%. For budgets between 200 and 5,000 field plot equivalents, P k > 75% was reached only for genotypes belonging to the best 5% of the population. As the optimum allocation for P k (5%) was similar to that for Δ G k , the choice of the optimization criterion was not crucial. The production costs of DHs had only a minor effect on the optimum number of locations and on values of the optimization criteria. [ABSTRACT FROM AUTHOR]

Characterization of genetic diversity of maize (Zea mays L.) germplasm is of great importance in hybrid maize breeding. The objectives of this study were to (i) investigate genetic diversity in CIMMYT subtropical, tropical midaltitude and highland inbreds with simple sequence repeat (SSR) markers, (ii) identify appropriate testers for the development of new inbred lines, (iii) compare this sample to U.S. and European elite maize lines and CIMMYT tropical lowland inbreds, and (iv) use the marker and pedigree information as a guide to understanding the heterotic relationship among the CIMMYT maize lines (CMLs) and their potential practical use in maize breeding pro- grams worldwide. Inbreds included in the study were assayed with 79 SSR markers. The CIMMYT inbred lines originated from 35 mostly broad-based populations and pools with mixed origins. A total of 566 alleles were scored, (averaging 7.2 and ranging from 2 to 16 alleles per locus). The modified Roger's distance (MRD) between pairs of inbreds averaged 0.78, with a range of 0.45 to 0.93. Unweighted paired group method using arithmetic averages (UPGMA) cluster analysis revealed no clear clustering. This reflects a mixed composition of CIMMYT subtropical, tropical midaltitude and highland maize populations and pools, and indicates that large amounts of variation have been incorporated into CIMMYT germplasm. Temperate heterotic groups were separated based on the markers, and nontemperate CIMMYT maize was genetically distinct from temperate lines. Discrete clusters were difficult to identify within and often between megaenvironments. Specific recommendations for nontemperate hybrid maize breeding are made. [ABSTRACT FROM AUTHOR]

Recent advances in RNA profiling offer an opportunity to establish functional links between genotype and phenotype for complex traits such as SCMV resistance. The change of RNA profiles was monitored on a macroarray containing SSH (suppression subtractive hybridization) clones. The number of differentially expressed genes (SCMV infected vs. non-infected) in individual lines was 177, 163, 165, 62, 47, 37, and 93, for FAP1360A, D21, D32, Pa405, F7, D145, and D408, respectively. All inbreds were divided into two groups by hierarchical cluster analysis: D32, D21, FAP1360A and D408 formed one; Pa405, D145, and F7 another group. Due to the genetic structure among the seven inbreds, genetic background and resistance response are confounded. With or without the resistant U.S. inbred line Pa405, 22 and 112 genes were identified by t tests between resistant (D21, D32, and FAP1360A) and susceptible (D145, D408, and F7) inbred lines, respectively. The 112 candidate genes were divided into three clusters by K-means clustering and analyzed in more detail, e.g., five genes were in silico mapped surrounding Scmv2 QTLs. These candidate genes provide a better understanding of signal transduction pathway for SCMV resistance and have the potential to develop functional markers to distinguish resistant and susceptible genotypes. [ABSTRACT FROM AUTHOR]

Detailed knowledge about the genetic diversity among germplasm is important for hybrid maize (Zea mays L.) breeding. The objectives of our study were to (i) investigate the genetic diversity among tropical lowland inbred lines and (ii) delimit heterotic groups in this germplasm. Simple sequence repeat (SSR) analysis of 79 markers distributed uniformly throughout the maize genome was performed for 155 tropical lowland inbred lines from the International Maize and Wheat Improvement Center (CIMMYT). Inbred lines were extracted from 60 broad-based populations and pools with mixed origin. We observed an average of 7.4 deles per marker with a range from 2 to 18. The polymorphic information content (PIC) of the 79 SSRs ranged from 0.13 to 0.87, with an average of 0.60. Cluster analysis of the tropical yellow and white lines revealed a lack of structure within this germplasm, which can be explained by the mixed origin of the populations used to extract these lines and the specific choice of testers for reciprocal recurrent selection (RRS). An SSR analysis can support the choice of representative testers for evaluating inbred lines in such broad-based populations. Thus, a more complete exploitation of the out-standing flint-dent heterotic pattern is possible. [ABSTRACT FROM AUTHOR]

In hybrid breeding the performance of lines in hybrid combinations is more important than their performance per se. Little information is available on the correlation between individual line and testcross (TC) performances for the resistance to European corn borer (ECB, Ostrinia nubilalis Hb.) in maize (Zea mays L.). Marker assisted selection (MAS) will be successful only if quantitative trait loci (QTL) found in F2 derived lines for ECB resistance are still expressed in hybrid combinations. The objectives of our study were: (1) to identify and characterize QTL for ECB resistance as well as agronomic and forage quality traits in a population of testcrossed F2:3 families; (2) to evaluate the consistency of QTL for per se and TC performances; and (3) to determine the association between per se and TC performances of F2:3 lines for these traits. Two hundred and four F2:3 lines were derived from the cross between maize lines D06 (resistant) and D408 (susceptible). These lines were crossed to D171 and the TC progenies were evaluated for ECB resistance and agronomic performance in two locations in 2000 and 2001. Using these TC progenies, six QTL for stalk damage rating (SDR) were found. These QTL explained 27.4% of the genotypic variance in a simultaneous fit. Three QTL for SDR were detected consistently for per se and TC performance. Phenotypic and genotypic correlations were low for per se and TC performance for SDR. Correlations between SDR and quality traits were not significant. Based on these results, we conclude that MAS will not be an efficient method for improving SDR. However, new molecular tools might provide the opportunity to use QTL data as a first step to identify genes involved in ECB resistance. Efficient MAS procedures might then be based on markers designed to trace and to combine specific genes and their alleles in elite maize breeding germplasm. [ABSTRACT FROM AUTHOR]

Eleven flint inbreds of maize were crossed with 11 dent inbreds according to a balanced incomplete factorial mating design to produce 66 single crosses (2W) in both reciprocal forms. Additionally, six three-way crosses (3W) were also produced in both reciprocal forms. These hybrids were evaluated for 11 forage yield and quality traits in 1983 and 1984 at three sites in Germany. Highly significant reciprocal differences were observed for nine traits in the 2W. The respective variance component estimates amounted to 2-33% of the variance component due to crosses. On average, flint x dent 2W had lower dry-matter content (DMC) than dent x flint 2W and a 1% greater dry-matter yield (DMY) of forage. Three-way crosses produced on singles exhibited greater DMC (3%) and DMY (5%) of the ear, metabolizable energy content (MEC) of stover (1%), and DMC and DMY of forage (2%) than their reciprocal forms produced on lines. Based on this study, because of their minor importance, routine testing for reciprocal differences among 2W hybrids is not recommended. [ABSTRACT FROM AUTHOR]

Development of multiple insect resistance in tropical maize represents a major effort of the maize breeding program at CIMMYT. Resistance to the southwestern corn borer (SWCB) is polygenically controlled with primarily additive gene action. Our main objective was to identify quantitative trait loci (QTL) involved in resistance to SWCB. Other objectives were to detect QTL in the same population for plant height, female flowering, and the anthesis-silking interval (ASI). A population of 472 F[SUB2] individuals derived from a cross between the susceptible line Ki3 and the resistant inbred CML139, was restriction fragment length polymorphism (RFLP) genotyped using 110 maize probes. F3 families were rated for leaf-feeding damage after artificial infestation at one location in three consecutive years. Height and flowering were measured in protected trials in two locations. QTL analyses were conducted using joint composite interval mapping. Seven QIL on chromosomes 3, 5, 6, 8, and 9 explained 30% of the phenotypic variance (σ[SUP2,SUBp]) for SWCB damage. Most QTL alleles conferring resistance were contributed from CML139. QTL showed dominance, partial dominance and additive gene action. Eleven QTL dispersed across the genome were determined to affect plant height and explained 43% of σ[SUP2,SUBp]. Four of these were in close proximity to loci with qualitative effects on plant height. Thirteen QTL (50% of σ[SUP2,SUBp]) were identified for days to female flowering and nine (30% of σ[SUP2,SUBp]) for ASI. Our results, along with those from other mapping studies at CIMMYT, are allowing us to formulate marker-assisted selection schemes to complement the breeding efforts for such complex traits as borer resistance. [ABSTRACT FROM AUTHOR]

The objective of this study was to investigate the origin of chromosome segments of maize (Zea mays L.) inbred B86 from its parental inbreds B52 and 0h43 using RFLPs. B86 was selected to combine resistance to the first and second brood of the European corn borer with the favorable agronomic performance of 0h43. RFLP analyses of the three inbreds were performed with three restriction enzymes (EcoRI, EcoRV, Hindlil) and 178 DNA probes covering all ten maize chromosomes. For two DNA probes in combination with one enzyme, B86 showed a new RFLP pattern not present in the two parents. Based on results from 119 polymorphic DNA probes, the proportion of the B86 genome contributed by B52 (51.3 %) and 0h43 (48.7 %) was almost equal. [ABSTRACT FROM AUTHOR]

Efficient production and use of doubled haploid lines can greatly accelerate genetic gains in maize breeding programs. One of the critical steps in standard doubled haploid line production is doubling the haploid genome using toxic and costly mitosis-inhibiting chemicals to achieve fertility in haploids. Alternatively, fertility may be spontaneously restored by natural chromosomal doubling, although generally at a rate too low for practical applications in most germplasm. This is the first large-scale genome-wise association study to analyze spontaneous chromosome doubling in haploids derived from tropical maize inbred lines. Induction crosses between tropicalized haploid inducers and 400 inbred lines were made, and the resulting haploid plants were assessed for haploid male fertility which refers to pollen production and haploid fertility which refers to seed production upon self-fertilization. A small number of genotypes were highly fertile and these fertility traits were highly heritable. Agronomic traits like plant height, ear height and tassel branch number were positively correlated with fertility traits. In contrast, haploid induction rate of the source germplasm and plant aspect were not correlated to fertility traits. Several genomic regions and candidate genes were identified that may control spontaneous fertility restoration. Overall, the study revealed the presence of large variation for both haploid male fertility and haploid fertility which can be potentially exploited for improving the efficiency of doubled haploid derivation in tropical maize germplasm. [ABSTRACT FROM AUTHOR]

Maize (Zea mays L.) grain yields have risen due to agronomic improvements and plant breeding, especially since the introduction of hybrid breeding. This study was conducted to measure the breeding progress within the flint heterotic pool of a public maize breeding program since the onset of hybrid breeding. Testcrosses with two dent testers of four flint founder lines (FL), four elite flint lines from three time periods each (EL1, EL2, EL3), and seven preselected doubled haploid (DH) lines from landraces (DH-LR) were evaluated together with four commercial check hybrids (CH). Grain yield (GY) and grain dry matter content (GDMC) were assessed in six diverse environments in southwestern Germany and northeastern France in 2016. We estimated a highly significant (P < 0.001) linear increase in GY of 48 kg ha−1 yr−1. The average testcross performance of DH-LR was significantly higher than of FL. Interestingly, two of the DH-LR lines had a higher yield than all EL2 lines. We conclude that a remarkable breeding progress has been achieved and annual gain in GY does not level off yet. However, an integration of new genetic material into the flint heterotic pool for maintaining sufficient genetic diversity is needed to ensure long-term selection gain. DH lines from landraces could be used for this purpose but we recommend using multiple test environments with contrasting yield levels and agronomic conditions as well as genetically broad testers to identify the most promising lines because interactions with testers and environments are larger in these materials compared with elite lines. [ABSTRACT FROM AUTHOR]

Maize (Zea mays L.) grain yields have risen due to agronomic improvements and plant breeding, especially since the introduction of hybrid breeding. This study was conducted to measure the breeding progress within the flint heterotic pool of a public maize breeding program since the onset of hybrid breeding. Testcrosses with two dent testers of four flint founder lines (FL), four elite flint lines from three time periods each (EL1, EL2, EL3), and seven preselected doubled haploid (DH) lines from landraces (DH-LR) were evaluated together with four commercial check hybrids (CH). Grain yield (GY) and grain dry matter content (GDMC) were assessed in six diverse environments in southwestern Germany and northeastern France in 2016. We estimated a highly significant (P < 0.001) linear increase in GY of 48 kg ha−1 yr−1. The average testcross performance of DH-LR was significantly higher than of FL. Interestingly, two of the DH-LR lines had a higher yield than all EL2 lines. We conclude that a remarkable breeding progress has been achieved and annual gain in GY does not level off yet. However, an integration of new genetic material into the flint heterotic pool for maintaining sufficient genetic diversity is needed to ensure long-term selection gain. DH lines from landraces could be used for this purpose but we recommend using multiple test environments with contrasting yield levels and agronomic conditions as well as genetically broad testers to identify the most promising lines because interactions with testers and environments are larger in these materials compared with elite lines. [ABSTRACT FROM AUTHOR]

Genomic selection is a well-investigated approach that facilitates and supports selection decisions for complex traits and has meanwhile become a standard tool in modern plant breeding. Phenomic selection has only recently been suggested and uses the same statistical procedures to predict the targeted traits but replaces marker data with near-infrared spectroscopy data. It may represent an attractive low-cost, high-throughput alternative but has not been sufficiently studied until now. Here, we used 400 genotypes of maize (Zea mays L.) comprising elite lines of the Flint and Dent heterotic pools as well as 6 Flint landraces, which were phenotyped in multienvironment trials for anthesis-silking-interval, early vigor, final plant height, grain dry matter content, grain yield, and phosphorus concentration in the maize kernels, to compare the predictive abilities of genomic as well as phenomic prediction under different scenarios. We found that both approaches generally achieved comparable predictive abilities within material groups. However, phenomic prediction was less affected by population structure and performed better than its genomic counterpart for predictions among diverse groups of breeding material. We therefore conclude that phenomic prediction is a promising tool for practical breeding, for instance when working with unknown and rather diverse germplasm. Moreover, it may make the highly monopolized sector of plant breeding more accessible also for low-tech institutions by combining well established, widely available, and cost-efficient spectral phenotyping with the statistical procedures elaborated for genomic prediction - while achieving similar or even better results than with marker data. [ABSTRACT FROM AUTHOR]

The ability to predict the agronomic performance of single-crosses with high precision is essential for selecting superior candidates for hybrid breeding. With recent technological advances, thousands of new parent lines, and, consequently, millions of new hybrid combinations are possible in each breeding cycle, yet only a few hundred can be produced and phenotyped in multi-environment yield trials. Well established prediction approaches such as best linear unbiased prediction (BLUP) using pedigree data and whole-genome prediction using genomic data are limited in capturing epistasis and interactions occurring within and among downstream biological strata such as transcriptome and metabolome. Because mRNA and small RNA (sRNA) sequences are involved in transcriptional, translational and post-translational processes, we expect them to provide information influencing several biological strata. However, using sRNA data of parent lines to predict hybrid performance has not yet been addressed. Here, we gathered genomic, transcriptomic (mRNA and sRNA) and metabolomic data of parent lines to evaluate the ability of the data to predict the performance of untested hybrids for important agronomic traits in grain maize. We found a considerable interaction for predictive ability between predictor and trait, with mRNA data being a superior predictor for grain yield and genomic data for grain dry matter content, while sRNA performed relatively poorly for both traits. Combining mRNA and genomic data as predictors resulted in high predictive abilities across both traits and combining other predictors improved prediction over that of the individual predictors alone. We conclude that downstream "omics" can complement genomics for hybrid prediction, and, thereby, contribute to more efficient selection of hybrid candidates. [ABSTRACT FROM AUTHOR]

A major application of genomic prediction (GP) in plant breeding is the identification of superior inbred lines within families derived from biparental crosses. When models for various traits were trained within related or unrelated biparental families (BPFs), experimental studies found substantial variation in prediction accuracy (PA), but little is known about the underlying factors. We used SNP marker genotypes of inbred lines from either elite germplasm or landraces of maize (Zea mays L.) as parents to generate in silico 300 BPFs of doubled-haploid lines. We analyzed PA within each BPF for 50 simulated polygenic traits, using genomic best linear unbiased prediction (GBLUP) models trained with individuals from either full-sib (FSF), half-sib (HSF), or unrelated families (URF) for various sizes (Ntrain) of the training set and different heritabilities (h²): In addition, we modified two deterministic equations for forecasting PA to account for inbreeding and genetic variance unexplained by the training set. Averaged across traits, PA was high within FSF (0.41-0.97) with large variation only for Ntrain <50 and h²,0:6: For HSF and URF, PA was on average 40-60% lower and varied substantially among different combinations of BPFs used for model training and prediction as well as different traits. As exemplified by HSF results, PA of across-family GP can be very low if causal variants not segregating in the training set account for a sizeable proportion of the genetic variance among predicted individuals. Deterministic equations accurately forecast the PA expected over many traits, yet cannot capture trait-specific deviations. We conclude that model training within BPFs generally yields stable PA, whereas a high level of uncertainty is encountered in across-family GP. Our study shows the extent of variation in PA that must be at least reckoned with in practice and offers a starting point for the design of training sets composed of multiple BPFs. [ABSTRACT FROM AUTHOR]

In vivo haploid induction (HI) triggered by pollination with special intraspecific genotypes, called inducers, is unique to Zea mays L. within the plant kingdom and has revolutionized maize breeding during the last decade. However, the molecular mechanisms underlying HI in maize are still unclear. To investigate the genetic basis of HI, we developed a new approach for genome-wide association studies (GWAS), termed conditional haplotype extension (CHE) test that allows detection of selective sweeps even under almost perfect confounding of population structure and trait expression. Here, we applied this test to identify genomic regions required for HI expression and dissected the combined support interval (50.34 Mb) of the QTL qhir1, detected in a previous study, into two closely linked genomic segments relevant for HI expression. The first, termed qhir11 (0.54 Mb), comprises an already fine-mapped region but was not diagnostic for differentiating inducers and noninducers. The second segment, termed qhir12 (3.97 Mb), had a haplotype allele common to all 53 inducer lines but not found in any of the 1482 noninducers. By comparing resequencing data of one inducer with 14 noninducers, we detected in the qhir12 region three candidate genes involved in DNA or amino acid binding, however, none for qhir11. We propose that the CHE test can be utilized in introgression breeding and different fields of genetics to detect selective sweeps in heterogeneous genetic backgrounds. [ABSTRACT FROM AUTHOR]

The efficiency of marker-assisted prediction of phenotypes has been studied intensively for different types of plant breeding populations. However, one remaining question is how to incorporate and counterbalance information from biparental and multiparental populations into model training for genome-wide prediction. To address this question, we evaluated testcross performance of 1652 doubled-haploid maize (Zea mays L.) lines that were genotyped with 56,110 single nucleotide polymorphism markers and phenotyped for five agronomic traits in four to six European environments. The lines are arranged in two diverse half-sib panels representing two major European heterotic germplasm pools. The data set contains 10 related biparental dent families and 11 related biparental flint families generated from crosses of maize lines important for European maize breeding. With this new data set we analyzed genome-based best linear unbiased prediction in different validation schemes and compositions of estimation and test sets. Further, we theoretically and empirically investigated marker linkage phases across multiparental populations. In general, predictive abilities similar to or higher than those within biparental families could be achieved by combining several half-sib families in the estimation set. For the majority of families, 375 half-sib lines in the estimation set were sufficient to reach the same predictive performance of biomass yield as an estimation set of 50 full-sib lines. In contrast, prediction across heterotic pools was not possible for most cases. Our findings are important for experimental design in genome-based prediction as they provide guidelines for the genetic structure and required sample size of data sets used for model training. [ABSTRACT FROM AUTHOR]