Testcross additive and dominance effects in best linear unbiased prediction of maize single-cross performance

Best linear unbiased prediction (BLUP) has been found to be useful in maize (Zea mays L.) breeding. The advantage of including both testcross additive and dominance effects (Intralocus Model) in BLUP, rather than only testcross additive effects (Additive Model), has not been clearly demonstrated. The objective of this study was to compare the usefulness of Intralocus and Additive Models for BLUP of maize single-cross performance. Multilocation data from 1990 to 1995 were obtained from the hybrid testing program of Limagrain Genetics. Grain yield, moisture, stalk lodging, and root lodging of untested single crosses were predicted from (1) the performance of tested single crosses and (2) known genetic relationships among the parental inbreds. Correlations between predicted and observed performance were obtained with a delete-one cross-validation procedure. For the Intralocus Model, the correlations ranged from 0.50 to 0.66 for yield, 0.88 to 0.94 for moisture, 0.47 to 0.69 for stalk lodging, and 0.31 to 0.45 for root lodging. The BLUP procedure was consistently more effective with the Intralocus Model than with the Additive Model. When the Additive Model was used instead of the Intralocus Model, the reductions in the correlation were largest for root lodging (0.06–0.35), smallest for moisture (0.00–0.02), and intermediate for yield (0.02–0.06) and stalk lodging (0.02–0.08). The ratio of dominance variance (v _D) to total genetic variance (v _G) was highest for root lodging (0.47) and lowest for moisture (0.10). The Additive Model may be used if prior information indicates that V_D for a given trait has little contribution to V_G. Otherwise, the continued use of the Intralocus Model for BLUP of single-cross performance is recommended.     

RFLP markers and predicted testcross performance of maize sister inbreds

 Inbreds selfed from the same F₂ or backcross population are referred to as sister inbreds. In some situations, maize (Zea mays L.) sister inbreds may not have testcross data available for best linear unbiased prediction (BLUP) of single-cross performance. This study evaluated the usefulness of BLUP and restriction fragment length polymorphism (RFLP)-based coefficients of coancestry ( f ) in predicting the testcross performance of sister inbreds. Parental contributions (p) were estimated from 70 RFLP loci for 15 inbreds that comprised three sister inbreds selfed from each of five F₂ populations. Estimates of p were subsequently used to calculate RFLP-based f. Grain yield, moisture, and stalk lodging data were obtained for 2265 single crosses tested by Limagrain Genetics in multilocation trials from 1990 to 1995. Performance of the sister inbreds when crossed to several inbred testers was predicted from the performance of the tested single crosses and RFLP-based f. Correlations between predicted and observed performance, obtained with a delete-one cross-validation procedure, were erratic and mostly low for all three traits. Correspondence was poor between ranks for predicted and observed general combining ability of the sister inbreds. The results suggested that the proportion of the genome derived by a sister inbred from a given parental inbred does not solely determine its testcross performance. The failure of BLUP and RFLP-based f to consistently predict testcross performance indicated that actual field testing will continue to be necessary for preliminary evaluation of sister inbreds. Received : 17 March 1997 / Accepted : 18 April 1997     

Molecular marker diversity among current and historical maize inbreds

Advanced-cycle pedigree breeding has caused maize (Zea mays L.) inbreds to become more-elite but more-narrow genetically. Our objectives were to evaluate the genetic distance among current and historical maize inbreds, and to estimate how much genetic diversity has been lost among current inbreds. We selected eight maize inbreds (B14, B37, B73, B84, Mo17, C103, Oh43 and H99) that largely represented the genetic background of current elite inbreds in the U.S. seed industry. A total of 32 other inbreds represented historical inbreds that were once important in maize breeding. Cluster analysis of the inbreds, using data for 83 SSR marker loci, agreed well with pedigree information. Inbreds from Iowa Stiff Stalk Synthetic (BSSS), Reid Yellow Dent, and Lancaster clustered into separate groups with only few exceptions. The average number of alleles per locus was 4.9 among all 40 inbreds and 3.2 among the eight current inbreds. The reduction in the number of alleles per locus was not solely due to sample size. The average genetic distance (D _ij ) was 0.65 among the eight current inbreds, 0.67 among the 32 historical inbreds, and 0.67 among all 40 inbreds. These differences were statistically insignificant. We conclude that genetic diversity among current inbreds has been reduced at the gene level but not at the population level. Hybrid breeding in maize maintained, rather than decreased, genetic diversity, at least during the initial subdivision of inbreds into BSSS and non-BSSS heterotic groups. We speculate, however, that exploiting other germplasm sources is necessary for sustaining long-term breeding progress in maize. Received: 21 August 2000 / Accepted: 5 January 2001     

Usefulness of Multiparental Populations of Maize (Zea mays L.) for Genome-Based Prediction

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.     

Genetic diversity among progenitors and elite lines from the Iowa Stiff Stalk Synthetic (BSSS) maize population: comparison of allozyme and RFLP data

Summary Data for restriction fragment length polymorphisms (RFLPs) of 144 clone-enzyme combinations and for 22 allozyme loci from 21 U.S. Corn Belt maize (Zea mays L.) inbreds were analyzed. The genetic materials included 14 progenitors of the Iowa Stiff Stalk Synthetic (BSSS) maize population, both parents of one missing BSSS progenitor, four elite inbreds derived from BSSS, and inbred Mo17. Objectives were to characterize the genetic variation among these 21 inbreds for both allozymes and RFLPs, to compare the results from both types of molecular markers, and to estimate the proportion of unique alleles in the BSSS progenitors. Genetic diversity among the 21 inbreds was substantially greater for RFLPs than for allozymes, but the percentages of unique RFLP variants (27%) and unique allozyme alleles (25%) in the BSSS progenitors were similar. Genetic distances between inbreds, estimated as Rogers' distance (RD), were, on average, twice as large for RFLP (0.51) as for allozyme data (0.24). RDs obtained from allozyme and RFLP data for individual line combinations were only poorly correlated (r = 0.23); possible reasons for discrepancies are discussed. Principal component analysis of RFLP data, in contrast to allozyme data, resulted in separate groupings of the ten BSSS progenitors derived from the Reid Yellow Dent population, the four BSSS elite lines, and Mo17. The remaining six BSSS progenitors were genetically rather diverse and contributed a large number of rare alleles to BSSS. The results of this study corroborate the fact that RFLPs are superior to allozymes for characterizing the genetic diversity of maize breeding materials, because of (1) the almost unlimited number of markers available and (2) the greater amount of polymorphisms found. In particular, RFLPs allow related lines and inbreds with common genetic background to be identified, but a large number of probe-enzyme combinations is needed to estimate genetic distances with the precision required.Joint contribution from Cereal and Soybean Research Unit, USDA, Agricultural Research Service, and Journal Paper No. J-14236 of the Iowa Agricultural and Home Economics Experiment Station, Projects 2818 and 2778     

A model for marker-assisted selection among single crosses with multiple genetic markers

 Trait means of marker genotypes are often inconsistent across experiments, thereby hindering the use of regression techniques in marker-assisted selection. Best linear unbiased prediction based on trait and marker data (TM-BLUP) does not require prior information on the mean effects associated with specific marker genotypes and, consequently, may be useful in applied breeding programs. The objective of this paper is to present a flanking-marker, TM-BLUP model that is applicable to interpopulation single crosses that characterize maize (Zea mays L.) breeding programs. The performance of a single cross is modeled as the sum of testcross additive and dominance effects at unmarked quantitative trait loci (QTL) and at marked QTL (MQTL). The TM-BLUP model requires information on the recombination frequencies between flanking markers and the MQTL and on MQTL variances. A tabular method is presented for calculating the conditional probability that MQTL alleles in two inbreds are identical by descent given the observed marker genotypes (G ^k _obs) at the kth MQTL. Information on identity by descent of MQTL alleles can then be used to calculate the conditional covariance of MQTL effects between single crosses given G ^k _obs. The inverse of the covariance matrix for dominance effects at unmarked QTL and MQTL can be written directly from the inverse of the covariance matrices of the corresponding testcross additive effects. In practice, the computations required in TM-BLUP may be prohibitive. The computational requirements may be reduced with simplified TM-BLUP models wherein dominance effects at MQTL are excluded, only the single crosses that have been tested are included, or information is pooled across several MQTL. Received: 22 June 1997 / Accepted: 25 February 1998     

Best linear unbiased prediction and optimum allocation of test resources in maize breeding with doubled haploids

With best linear unbiased prediction (BLUP), information from genetically related candidates is combined to obtain more precise estimates of genotypic values of test candidates and thereby increase progress from selection. We developed and applied theory and Monte Carlo simulations implementing BLUP in 2 two-stage maize breeding schemes and various selection strategies. Our objectives were to (1) derive analytical solutions of the mixed model equations under two breeding schemes, (2) determine the optimum allocation of test resources with BLUP under different assumptions regarding the variance component ratios for grain yield in maize, (3) compare the progress from selection using BLUP and conventional phenotypic selection based on mean performance solely of the candidates, and (4) analyze the potential of BLUP for further improving the progress from selection. The breeding schemes involved selection for testcross performance either of DH lines at both stages (DHTC) or of S₁ families at the first stage and DH lines at the second stage (S₁TC-DHTC). Our analytical solutions allowed much faster calculations of the optimum allocations and superseded matrix inversions to solve the mixed model equations. Compared to conventional phenotypic selection, the progress from selection was slightly higher with BLUP for both optimization criteria, namely the selection gain and the probability to select the best genotypes. The optimum allocation of test resources in S₁TC-DHTC involved ≥10 test locations at both stages, a low number of crosses (≤6) each with 100–300 S₁ families at the first stage, and 500–1,000 DH lines at the second stage. In breeding scheme DHTC, the optimum number of test candidates at the first stage was 5–10 times larger, whereas the number of test locations at the first stage and the number of test candidates at the second stage were strongly reduced compared to S₁TC-DHTC.     

Genetic diversity of maize inbred lines within and among heterotic groups revealed by RFLPs

Summary The objectives of this study were (1) to investigate genetic diversity for RFLPs in a set of important maize inbreds commonly used in Italian breeding programs, (2) to compare genetic similarities between unrelated lines from the same and different heterotic groups, and (3) to examine the potential of RFLPs for assigning maize inbreds to heterotic groups. Forty inbreds were analyzed for RFLPs with two restriction enzymes (EcoRI and HindIII) and 82 DNA clones uniformly distributed over the maize genome. Seventy clone-enzyme combinations gave single-banded RFLP patterns, and 79 gave multiple-banded RFLP patterns. The average number of RFLP patterns detected per clone-enzyme combination across all inbreds was 5.8. RFLP data revealed a wide range of genetic diversity within the two heterotic groups assayed, Iowa Stiff Stalk Synthetic (BSSS) and Lancaster Sure Crop (LSC). Genetic similarity (GS) between lines was estimated from binary RFLP data according to the method of Nei and Li (1979). The mean GS for line combinations of type BSSS × LSC (0.498) was substantially smaller than for unrelated line combinations or type BSSS × BSSS (0.584) but almost as great as for un-related line combinations of type LSC × LSC (0.506). Principal coordinate and cluster analyses based on GS values resulted in the separate groupings of lines, which is consistent with known pedigree information. A comparison between both methods for multivariate analyses of RFLP data is presented.     

Accuracy of genotypic value predictions for marker-based selection in biparental plant populations

The availability of cheap and abundant molecular markers has led to plant-breeding methods that rely on the prediction of genotypic value from marker data, but published information is lacking on the accuracy of genotypic value predictions with empirical data in plants. Our objectives were to (1) determine the accuracy of genotypic value predictions from multiple linear regression (MLR) and genomewide selection via best linear unbiased prediction (BLUP) in biparental plant populations; (2) assess the accuracy of predictions for different numbers of markers (N _M) and progenies (N _P) used in estimation; and (3) determine if an empirical Bayes approach for modeling of the variances of individual markers and of epistatic effects leads to more accurate predictions in empirical data. We divided each of four maize (Zea mays L.) datasets, one Arabidopsis dataset, and two barley (Hordeum vulgare L.) datasets into an estimation set, where marker effects were calculated, and a test set, where genotypic values were predicted based on markers. Predictions were more accurate with BLUP than with MLR. Predictions became more accurate as N _P and N _M increased, until sufficient genome coverage was reached. Modeling marker variances with the empirical Bayes method sometimes led to slightly better predictions, but the accuracy with different variants of the empirical Bayes method was often inconsistent. In nearly all cases, the accuracy with BLUP was not significantly different from the highest accuracy across all methods. Accounting for epistasis in the empirical Bayes procedure led to poorer predictions. We concluded that among the methods considered, the quick and simple BLUP approach is the method of choice for predicting genotypic value in biparental plant populations.     

Genetic diversity for restriction fragment length polymorphisms and heterosis for two diallel sets of maize inbreds

Summary Changes that may have occurred over the past 50 years of hybrid breeding in maize (Zea maize L.) with respect to heterosis for yield and heterozygosity at the molecular level are of interest to both maize breeders and quantitative geneticists. The objectives of this study were twofold: The first, to compare two diallels produced from six older maize inbreds released in the 1950's and earlier and six newer inbreds released during the 1970's with respect to (a) genetic variation for restriction fragment length polymorphisms (RFLPs) and (b) the size of heterosis and epistatic effects, and the second, to evaluate the usefulness of RFLP-based genetic distance measures in predicting heterosis and performance of single-cross hybrids. Five generations (parents, F₁; F₂, and backcrosses) from the 15 crosses in each diallel were evaluated for grain yield and yield components in four Iowa environments. Genetic effects were estimated from generation means by ordinary diallel analyses and by the Eberhart-Gardner model. Newer lines showed significantly greater yield for inbred generations than did older lines but smaller heterosis estimates. In most cases, estimates of additive x additive epistatic effects for yield and yield components were significantly positive for both groups of lines. RFLP analyses of inbred lines included two restriction enzymes and 82 genomic DNA clones distributed over the maize genome. Eighty-one clones revealed polymorphisms with at least one enzyme. In each set, about three different RFLP variants were typically found per RFLP locus. Genetic distances between inbred lines were estimated from RFLP data as Rogers' distance (RD), which was subdivided into general (GRD) and specific (SRD) Rogers' distances within each diallel. The mean and range of RDs were similar for the older and newer lines, suggesting that the level of heterozygosity at the molecular level had not changed. GRD explained about 50% of the variation among RD values in both sets. Cluster analyses, based on modified Rogers' distances, revealed associations among lines that were generally consistent with expectations based on known pedigree and on previous research. Correlations of RD and SRD with f₁ performance, specific combining ability, and heterosis for yield and yield components, were generally positive, but too small to be of predictive value. In agreement with previous studies, our results suggest that RFLPs can be used to investigate relationships among maize inbreds, but that they are of limited usefulness for predicting the heterotic performance of single crosses between unrelated lines.Joint contribution from Cereal and Soybean Research Unit, USDA, Agricultural Research Service and Journal Paper no. J-13929 of the Iowa Agric and Home Economics Exp Stn, Ames, IA 50011. Projects no. 2818 and 2778A.E.M. is presently at the Iowa State University on leave from University of Hohenheim, D-7000 Stuttgart 70, Federal Republic of Germany     

Prediction of testcross means and variances among F3 progenies of F1 crosses from testcross means and genetic distances of their parents in maize

 Prediction of the means and genetic variances in segregating generations could help to assess the breeding potential of base populations. In this study, we investigated whether the testcross (TC) means and variances of F₃ progenies from F₁ crosses in European maize can be predicted from the TC means of their parents and F₁ crosses and four measures of parental genetic divergence: genetic distance (GD) determined by 194 RFLP or 691 AFLP^{TM 1} markers, mid-parent heterosis (MPH), and absolute difference between the TC means of parents (∣P₁−P₂∣). The experimental materials comprised six sets of crosses; each set consisted of four elite inbreds from the flint or dent germplasm and the six possible F₁ crosses between them, which were evaluated for mid-parent heterosis. Testcross progenies of these materials and 20 random F₃ plants per F₁ cross were produced with a single-cross tester from the opposite heterotic group and evaluated in two environments. The characters studied were plant height, dry matter content and grain yield. The genetic distance between parent lines ranged between 0.17 and 0.70 for RFLPs and between 0.14 and 0.57 for AFLPs in the six sets. Testcross-means of parents, F₁ crosses, and F₃ populations averaged across the six crosses in a particular set generally agreed well for all three traits. Bartlett’s test revealed heterogeneous TC variances among the six crosses in all sets for plant height, in four sets for grain yield and in five sets for dry matter content. Correlations among the TC means of the parents, F₁ crosses, and F₃ populations were highly significant and positive for all traits. Estimates of the TC variance among F₃ progenies for the 36 crosses showed only low correlations with the four measures of parental genetic divergence for all traits. The results demonstrated that for our material, the TC means of the parents or the parental F₁ cross can be used as predictors for the TC means of F₃ populations. However, the prediction of the TC variance remains an unsolved problem. Received: 4 August 1997 / Accepted: 17 November 1997     

Association between line per se and testcross performance for eight agronomic and quality traits in winter rye

Key message

We investigated associations between line per se and testcross performance in rye and suggested that selection for per se performance is valuable for several traits in multi-stage selection programs.

Abstract

Genotypic correlation between line per se and testcross performance is an important quantitative-genetic parameter for optimizing hybrid breeding programs. The main goal of this survey was to study the association of line per se and testcross performance at the phenotypic level. We used experimental data from the line per se and testcross performance of two segregating winter rye populations (A, B) with each of 220 progenies tested in six environments for eight agronomic and quality traits. Genotypic variances were considerably larger for per se than for testcross performance of all investigated traits resulting in higher heritabilities of the former in most instances. Genotypic correlations (r _g) between testcross and line per se performance decreased with increasing complexity of the trait as shown by the respective heritabilities. They were highest (r _g ≥ 0.7) for plant height and test weight in population B, and thousand-kernel weight, falling number and starch content in both populations. A selection of these traits for line per se performance in early generations will save field plots in further testing testcross performance and increase efficiency of hybrid breeding.     

Change in ribosomal DNA intergenic spacer-length composition in maize recurrent selection populations. 1. Analysis of BS13, BSSS,and BSCB1

Five different ribosomal DNA (rDNA) intergenic spacer-length variants (slvs) were detected among the maize inbreds which were the progenitors of Iowa Stiff Stalk Synthetic (BSSS). One rDNASstI restriction site polymorphism in the 3 region of the 26S gene was detected. Nine different rDNA intergenic spacer (IGS) hybridization fragment patterns (assigned letter designations A-I) were observed among the BSSS progenitors. Following 7 cycles of half-sib recurrent selection in BSSS using the Ia13 double cross as a tester, hybridization fragment pattern E became predominant in the population. In contrast, 11 cycles of reciprocal recurrent selection in BSSS with the Iowa Corn Borer Synthetic No. 1 (BSCB1) population resulted in hybridization pattern D becoming predominant. Hybridization pattern E is present in the elite inbreds B14, B37, B73, and B84, which were derived from different cycles of the BSSS half-sib recurrent selection program with Ia13. Hybridization pattern D is present in the elite inbreds B89 and B94, which were derived from different cycles of the BSSS reciprocal recurrent selection program with BSCB1. Therefore, two different forms of recurrent selection on BSSS resulted in different hybridization patterns becoming predominant in the selected populations and present in elite inbreds derived from the populations. These results also suggest that rDNA IGS hybridization fragment patterns D and E, which both have the longest slv detected, may have a selective or adaptive advantage in BSSS materials grown in the Corn Belt.     

Procedures for identifying S-allele genotypes of Brassica

Summary Procedures are described for efficient selection of: (1) homozygous and heterozygous S-allele genotypes; (2) homozygous inbreds with the strong self- and sib-incompatibility required for effective seed production of single-cross F₁ hybrids; (3) heterozygous genotypes with the high self- and sib-incompatibility required for effective seed production of 3- and 4-way hybrids.From reciprocal crosses between two first generation inbred (I₁) plants there are three potential results: both crosses are incompatible; one is incompatible and the other compatible; and both are compatible. Incompatibility of both crosses is useful information only when combined with data from other reciprocal crosses. Each compatible cross, depending on whether its reciprocal is incompatible or compatible, dictates alternative reasoning and additional reciprocal crosses for efficiently and simultaneously identifying: (A) the S-allele genotype of all individual I₁ plants, and (B) the expressions of dominance or codominance in pollen and stigma (sexual organs) of an S-allele heterozygous genotype. Reciprocal crosses provide the only efficient means of identifying S-allele genotypes and also the sexual-organ x S-allele-interaction types.Fluorescent microscope assay of pollen tube penetration into the style facilitates quantitation within 24–48 hours of incompatibility and compatibility of the reciprocal crosses. A procedure for quantitating the reciprocal difference is described that maximizes informational content of the data about interactions between S alleles in pollen and stigma of the S-allele-heterozygous genotype.Use of the non-inbred I_o generation parent as a known heterozygous S-allele genotype in crosses with its first generation selfed (I₁) progeny usually reduces at least 7 fold the effort required for achieving objectives 1, 2, and 3, compared to the method of making reciprocal crosses only among I₁ plants.Identifying the heterozygous and both homozygous S-allele genotypes during the I₁ generation facilitates, during subsequent inbred generations, strong selection for or against modifier genes that influence the intensity of self- and sib-incompatibility. Selection for strong self and sib incompatibility can be effective for both homozygous inbreds and also for the S-allele heterozygote, thus facilitating production of single-cross F₁ hybrids and also of 3-and 4-way hybrids.Department of Plant Breeding and Biometry paper No. 690     

Additive and testcross genetic variances in crosses among recombinant inbreds

 Breeders desire populations with a high mean performance and a large genetic variance. Theory and methods are lacking for predicting additive variance (V _A ) and testcross variance (V _T ) in biparental populations. Breeders have unsuccessfully attempted to predict V _A based on the coefficient of coancestry ( f ) or molecular-marker similarity between parents. In this paper, we derive the expected values of V _A and V _T in biparental populations, examine the variability of V _A among biparental crosses, and discuss how V _A and V _T may be predicted in applied breeding programs. Suppose i is a recombinant inbred derived from the cross between inbreds P ₁ and P ₂, and inbred j is not a direct descendant of i. Let V _A(i,j) be the additive variance in the F₂ of the (i×j) biparental cross. Let V _T(i, j) be the variance among testcrosses of F₂ individuals with a specific unrelated inbred or population. Assuming linkage equilibrium and the absence of epistasis, V _A(i, j) =λV _A(P1, j) +(1−λ) V _A(P2, j) , where λ= parental contribution of P ₁ to i. Similarly, V _T(i, j) = λV _T(P1, j) +(1−λ) V _T(P2, j) . Additive variance in crosses between recombinant inbreds cannot be modelled as a function of  f if, as indicated in the literature, V _A differs among crosses of founder inbreds. If molecular-marker similarity between parents is used as an estimate of f, then a strong linear relationship is likewise not expected between V _A and marker similarity. Differences between the actual and expected λ led to variation in V _A . In applied breeding programs, modelling V _A or V _T in biparental crosses may be feasible with estimates of V _A or V _T in prior crosses and information on λ obtained from molecular-marker data. Received: 23 September 1997 / Accepted: 30 December 1997     

Genomic Prediction of Testcross Performance in Canola (Brassica napus)

Genomic selection (GS) is a modern breeding approach where genome-wide single-nucleotide polymorphism (SNP) marker profiles are simultaneously used to estimate performance of untested genotypes. In this study, the potential of genomic selection methods to predict testcross performance for hybrid canola breeding was applied for various agronomic traits based on genome-wide marker profiles. A total of 475 genetically diverse spring-type canola pollinator lines were genotyped at 24,403 single-copy, genome-wide SNP loci. In parallel, the 950 F1 testcross combinations between the pollinators and two representative testers were evaluated for a number of important agronomic traits including seedling emergence, days to flowering, lodging, oil yield and seed yield along with essential seed quality characters including seed oil content and seed glucosinolate content. A ridge-regression best linear unbiased prediction (RR-BLUP) model was applied in combination with 500 cross-validations for each trait to predict testcross performance, both across the whole population as well as within individual subpopulations or clusters, based solely on SNP profiles. Subpopulations were determined using multidimensional scaling and K-means clustering. Genomic prediction accuracy across the whole population was highest for seed oil content (0.81) followed by oil yield (0.75) and lowest for seedling emergence (0.29). For seed yieId, seed glucosinolate, lodging resistance and days to onset of flowering (DTF), prediction accuracies were 0.45, 0.61, 0.39 and 0.56, respectively. Prediction accuracies could be increased for some traits by treating subpopulations separately; a strategy which only led to moderate improvements for some traits with low heritability, like seedling emergence. No useful or consistent increase in accuracy was obtained by inclusion of a population substructure covariate in the model. Testcross performance prediction using genome-wide SNP markers shows considerable potential for pre-selection of promising hybrid combinations prior to resource-intensive field testing over multiple locations and years.     

Genetic diversity for RFLPs in European maize inbreds

Summary Restriction fragment length polymorphisms (RFLPs) have been proposed for the prediction of the yield potential of hybrids and the assignment of inbreds to heterotic groups. Such use was investigated in 66 diallel crosses among 6 flint and 6 dent inbreds from European maize (Zea mays L.) germ plasm. Inbreds and hybrids were evaluated for seven forage traits in four environments in the Federal Republic of Germany. Midparent heterosis (MPH) and specific combining ability (SCA) were calculated. Genetic distances (GD) between lines were calculated from RFLP data of 194 clone-enzyme combinations. GDs were greater for flint x dent than for flint x flint and dent x dent line combinations. Cluster analysis based on GDs showed separate groupings of flint and dent lines and agreed with pedigree information, except for 1 inbred. GDs of all line combinations in the diallel were partitioned into general (GGD) and specific (SGD) genetic distances; GGD explained approximately 20% of the variation among GD values. For the 62 diallel crosses (excluding 4 crosses of highly related lines), correlations of GD with F₁ performance, MPH, and SCA for dry matter yield (DMY) of stover, ear, and forage were positive but mostly of moderate size (0.09r0.60) compared with the higher correlations (0.39r0.77) of SGD with these traits. When separate calculations were performed for various subsets, correlations of GD and SGD with DMY traits were generally small (r<0.47) for the 36 flint x dent crosses, significantly positive (r<0.53) for the 14 flint x flint crosses, and inconclusive for the 12 dent x dent crosses because of the lack of significant genotypic variation. Results indicated that RFLPs can be used for assigning inbreds to heterotic groups. RFLP-based genetic distance measures seem to be useful for predicting forage yield of (1) crosses between lines from the same germ plasm group or (2) crosses including line combinations from the same as well as different heterotic groups. However, they are not indicative of the hybrid forage yield of crosses between unrelated lines from genetically divergent heterotic groups.     

Genetics of resistance to the pink stem borer (Sesamia nonagrioides) in maize (Zea mays)

Our knowledge of the genetics of resistance to the pink stem borer ( Sesamia nonagrioides ) in maize ( Zea mays ) is restricted to a few crosses among maize inbreds. The objectives of this study were to enlarge our understanding of the genetics of traits related to damage by pink stem borer and yield under infestation and to use generation means analyses to compare per se and testcross performance for detecting epistatic effects. All generations, either per se or crossed to testers, were evaluated in a 10 × 10 triple lattice design under artificial infestation with S. nonagrioides in 2005 and 2006. Most traits fit an additive–dominance model; but evidence for epistasis for resistance and yield under infestation was shown. Epistasis, in general, did not appear to play an important role in the inheritance of yield under pink stem borer infestation. However, the epistasis contribution to maize yield performance could be important in some outstanding crosses such as EP42 × A637. Testcross generation means revealed epistatic effects undetected by the generation means analysis, but neither method was able to eliminate dominance effects that could prevail over epistatic effects.     

Broadening the genetic base of European maize heterotic pools with US Cornbelt germplasm using field and molecular marker data

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.     

Molecular marker-based prediction of hybrid performance in maize using unbalanced data from multiple experiments with factorial crosses

In hybrid breeding, the prediction of hybrid performance (HP) is extremely important as it is difficult to evaluate inbred lines in numerous cross combinations. Recent developments such as doubled haploid production and molecular marker technologies have enhanced the prospects of marker-based HP prediction to accelerate the breeding process. Our objectives were to (1) predict HP using a combined analysis of hybrids and parental lines from a breeding program, (2) evaluate the use of molecular markers in addition to phenotypic and pedigree data, (3) evaluate the combination of line per se data with marker-based estimates, (4) study the effect of the number of tested parents, and (5) assess the advantage of haplotype blocks. An unbalanced dataset of 400 hybrids from 9 factorial crosses tested in different experiments and data of 79 inbred parents were subjected to combined analyses with a mixed linear model. Marker data of the inbreds were obtained with 20 AFLP primer–enzyme combinations. Cross-validation was used to assess the performance prediction of hybrids of which no or only one parental line was testcross evaluated. For HP prediction, the highest proportion of explained variance (R ²), 46% for grain yield (GY) and 70% for grain dry matter content (GDMC), was obtained from line per se best linear unbiased prediction (BLUP) estimates plus marker effects associated with mid-parent heterosis (TEAM-LM). Our study demonstrated that HP was efficiently predicted using molecular markers even for GY when testcross data of both parents are not available. This can help in improving greatly the efficiency of commercial hybrid breeding programs.