Breeding maize as biogas substrate in Central Europe: I. Quantitative-genetic parameters for testcross performance.

Biofuels have gained importance recently and the use of maize biomass as substrate in biogas plants for production of methane has increased tremendously in Germany. The objectives of our research were to (1) estimate variance components and heritability for different traits relevant to biogas production in testcrosses (TCs) of maize, (2) study correlations among traits, and (3) discuss strategies to breed maize as a substrate for biogas fermenters. We evaluated 570 TCs of 285 diverse dent maize lines crossed with two flint single-cross testers in six environments. Data were recorded on agronomic and quality traits, including dry matter yield (DMY), methane fermentation yield (MFY), and methane yield (MY), the product of DMY and MFY, as the main target trait. Estimates of variance components showed general combining ability (GCA) to be the major source of variation. Estimates of heritability exceeded 0.67 for all traits and were even much greater in most instances. Methane yield was perfectly correlated with DMY but not with MFY, indicating that variation in MY is primarily determined by DMY. Further, DMY had a larger heritability and coefficient of genetic variation than MFY. Hence, for improving MY, selection should primarily focus on DMY rather than MFY. Further, maize breeding for biogas production may diverge from that for forage production because in the former case, quality traits seem to be of much lower importance.

Breeding maize as biogas substrate in Central Europe: II. Quantitative-genetic parameters for inbred lines and correlations with testcross performance.

Breeding maize for use as a biogas substrate (biogas maize) has recently gained considerable importance. To optimize hybrid breeding programs, information about line per se performance (LP) of inbreds and its relation to their general combining ability (GCA) is required. The objectives of our research were to (1) estimate variance components and heritability of LP for agronomic and quality traits relevant to biogas production, (2) study correlations among traits as well as between LP and GCA, and (3) discuss implications for breeding of biogas maize. We evaluated 285 diverse dent maize inbred lines in six environments. Data were recorded on agronomic and quality traits, including dry matter yield (DMY), methane fermentation yield (MFY), and their product, methane yield (MY), as the main target trait. In agreement with observations made for GCA in a companion study, variation in MY was mainly determined by DMY. MFY, which showed moderate correlation with lignin but only weak correlation with starch, revealed only low genotypic variation. Thus, our results favor selection of genotypes with high DMY and less focus on ear proportion for biogas maize. Genotypic correlations between LP and GCA [r (g) (LP, GCA)] were highest (≥0.94) for maturity traits (days to silking, dry matter concentration) and moderate (≥0.65) for DMY and MY. Multistage selection is recommended. Selection for GCA of maturity traits, plant height, and to some extent also quality traits and DMY on the level of LP looks promising.

Gene stacking strategies with doubled haploids derived from biparental crosses: theory and simulations assuming a finite number of loci.

Recent progress in genotyping and doubled haploid (DH) techniques has created new opportunities for development of improved selection methods in numerous crops. Assuming a finite number of unlinked loci (ℓ) and a given total number (n) of individuals to be genotyped, we compared, by theory and simulations, three methods of marker-assisted selection (MAS) for gene stacking in DH lines derived from biparental crosses: (1) MAS for high values of the marker score (T, corresponding to the total number of target alleles) in the F(2) generation and subsequently among DH lines derived from the selected F(2) individual (Method 1), (2) MAS for augmented F(2) enrichment and subsequently for T among DH lines from the best carrier F(2) individual (Method 2), and (3) MAS for T among DH lines derived from the F(1) generation (Method 3). Our objectives were to (a) determine the optimum allocation of resources to the F(2) ([Formula: see text]) and DH generations [Formula: see text] for Methods 1 and 2 by simulations, (b) compare the efficiency of all three methods for gene stacking by simulations, and (c) develop theory to explain the general effect of selection on the segregation variance and interpret our simulation results. By theory, we proved that for smaller values of ℓ, the segregation variance of T among DH lines derived from F(2) individuals, selected for high values of T, can be much smaller than expected in the absence of selection. This explained our simulation results, showing that for Method 1, it is best to genotype more F(2) individuals than DH lines ([Formula: see text]), whereas under Method 2, the optimal ratio [Formula: see text] was close to 0.5. However, for ratios deviating moderately from the optimum, the mean [Formula: see text] of T in the finally selected DH line ([Formula: see text]) was hardly reduced. Method 3 had always the lowest mean [Formula: see text] of [Formula: see text] except for small numbers of loci (ℓ = 4) and is favorable only if a small number of loci are to be stacked in one genotype and/or saving one generation is of crucial importance in cultivar development. Method 2 is under most circumstances the superior method, because it generally showed the highest mean [Formula: see text] and lowest SD of [Formula: see text] for the finally selected DH.

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 S(1) families at the first stage and DH lines at the second stage (S(1)TC-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 S(1)TC-DHTC involved ≥ 10 test locations at both stages, a low number of crosses (≤ 6) each with 100-300 S(1) 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 S(1)TC-DHTC.

Extent and genome-wide distribution of linkage disequilibrium in commercial maize germplasm.

Association mapping is based on linkage disequilibrium (LD) resulting from historical recombinations and helps understanding the genetic basis of complex traits. Many factors affect LD and, therefore, it must be determined empirically in the germplasm under investigation to examine the prospects of successful genome-wide association mapping. The objectives of our study were to (1) examine the extent of LD with simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers in 1,537 commercial maize inbred lines belonging to four heterotic pools, (2) compare the LD patterns determined by these two marker types, (3) evaluate the number of SNP markers needed to perform genome-wide association analyses, and (4) investigate temporal trends of LD. Mean values of the squared correlation coefficient ([Formula: see text]) were almost identical for unlinked, linked, and adjacent SSR marker pairs. In contrast, [Formula: see text] values were lowest for the unlinked SNP loci and highest for the SNPs within amplicons. LD decay varied across the different heterotic pools and the individual chromosomes. The SSR markers employed in the present study are not adequate for association analysis, because of insufficient marker density for the germplasm evaluated. Based on the decay of LD in the various heterotic pools, we would need between 4,000 and 65,000 SNP markers to detect with a reasonable power associations with rather large quantitative trait loci (QTL). A much higher marker density is required to identify QTL with smaller effects. However, not only the total number of markers but also their distribution among and along the chromosomes are primordial for undertaking powerful association analyses.

Prediction of hybrid performance in maize using molecular markers and joint analyses of hybrids and parental inbreds.

The identification of superior hybrids is important for the success of a hybrid breeding program. However, field evaluation of all possible crosses among inbred lines requires extremely large resources. Therefore, efforts have been made to predict hybrid performance (HP) by using field data of related genotypes and molecular markers. In the present study, the main objective was to assess the usefulness of pedigree information in combination with the covariance between general combining ability (GCA) and per se performance of parental lines for HP prediction. In addition, we compared the prediction efficiency of AFLP and SSR marker data, estimated marker effects separately for reciprocal allelic configurations (among heterotic groups) of heterozygous marker loci in hybrids, and imputed missing AFLP marker data for marker-based HP prediction. Unbalanced field data of 400 maize dent x flint hybrids from 9 factorials and of 79 inbred parents were subjected to joint analyses with mixed linear models. The inbreds were genotyped with 910 AFLP and 256 SSR markers. Efficiency of prediction (R (2)) was estimated by cross-validation for hybrids having no or one parent evaluated in testcrosses. Best linear unbiased prediction of GCA and specific combining ability resulted in the highest efficiencies for HP prediction for both traits (R (2) = 0.6-0.9), if pedigree and line per se data were used. However, without such data, HP for grain yield was more efficiently predicted using molecular markers. The additional modifications of the marker-based approaches had no clear effect. Our study showed the high potential of joint analyses of hybrids and parental inbred lines for the prediction of performance of untested hybrids.

High congruency of QTL positions for heterosis of grain yield in three crosses of maize.

The genetic basis of heterosis in maize has been investigated in a number of studies but results have not been conclusive. Here, we compare quantitative trait loci (QTL) mapping results for grain yield, grain moisture, and plant height from three populations derived from crosses of the heterotic pattern Iowa Stiff Stalk Synthetic x Lancaster Sure Crop, investigated with the Design III, and analyzed with advanced statistical methods specifically developed to examine the genetic basis of mid-parent heterosis (MPH). In two populations, QTL analyses were conducted with a joint fit of linear transformations Z (1) (trait mean across pairs of backcross progenies) and Z (2) (half the trait difference between pairs of backcross progenies) to estimate augmented additive and augmented dominance effects of each QTL, as well as their ratio. QTL results for the third population were obtained from the literature. For Z (2) of grain yield, congruency of QTL positions was high across populations, and a large proportion of the genetic variance (~70%) was accounted for by QTL. This was not the case for Z (1) or the other two traits. Further, almost all congruent grain yield QTL were located in the same or an adjacent bin encompassing the centromere. We conclude that different alleles have been fixed in each heterotic pool, which in combination with allele(s) from the opposite heterotic pool lead to high MPH for grain yield. Their positive interactions very likely form the base line for the superior performance of the heterotic pattern under study.

Variation of the parental genome contribution in segregating populations derived from biparental crosses and its relationship with heterosis of their Design III progenies.

The variation of the parental genome contribution (PGC) and its relationship with the genetic architecture of heterosis have received little attention. Our objectives were to (1) derive formulas for the variance of PGC in selfing, backcross (BC) or intermated generations produced from biparental crosses of homozygous parents, (2) investigate the correlation [Formula: see text] of the PGC [Formula: see text] estimated by a set M of markers, with Z (2) (half the trait difference between each pair of BC progenies) in the Design III, and (3) interpret experimental results on this correlation with regard to the genetic basis of heterosis. Under all mating systems, the variance of PGC is smaller in species with a larger number and more uniform length of chromosomes. It decreases with intermating and backcrossing but increases under selfing. The ratio of variances of PGC in F(1)DH (double haploids), F(2) and BC(1) populations is 4:2:1, but it is smaller in advanced selfing generations than expected for quantitative traits. Thus, altering the PGC by marker-assisted selection for the genetic background is more promising (i) in species with a smaller number and/or shorter chromosomes and (ii) in F(2) than in progenies of later selfing generations. The correlation [Formula: see text] depends on the linkage relationships between M and the QTL influencing Z(2) as well as the augmented dominance effects [Formula: see text] of the QTL, which include dominance and additive x additive effects with the genetic background, and sum up to mid-parent heterosis. From estimates of [Formula: see text] as well as QTL studies, we conclude that heterosis for grain yield in maize is caused by the action of numerous QTL distributed across the entire genome with positive [Formula: see text] effects.

Dissection of the genetic basis of heterosis in an elite maize hybrid by QTL mapping in an immortalized F2 population.

The genetic basis of heterosis for grain yield and its components was investigated at the single- and two-locus levels using molecular markers with an immortalized F(2) (IF(2)) population, which was developed by pair crosses among recombinant inbred lines (RILs) derived from the elite maize hybrid Yuyu22. Mid-parent heterosis of each cross in the IF(2) population was used to map heterotic quantitative trait loci. A total of 13 heterotic loci (HL) were detected. These included three HL for grain yield, seven for ear length, one for ear row number and two for 100-kernel weight. A total of 143 digenic interactions contributing to mid-parent heterosis were detected at the two-locus level involving all three types of interactions (additive x additive = AA, additive x dominance = AD or DA, dominance x dominance = DD). There were 25 digenic interactions for grain yield, 36 for ear length, 31 for ear row number and 51 for 100-kernel weight. Altogether, dominance effects of HL at the single-locus level as well as AA interactions played an important role in the genetic basis of heterosis for grain yield and its components in Yuyu22.

Hybrid maize breeding with doubled haploids: V. Selection strategies for testcross performance with variable sizes of crosses and S(1) families.

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 S(0) plants in the parental cross or via S(1) 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 S(1) families. We examined the optimum allocation of resources to maximize the selection gain DeltaG 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 S(1) 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) S(1) families in the first stage and of DH lines within S(1) families in the second stage (S(1)TC-DHTC) with uniform and variable sizes of crosses and S(1) families. We developed and employed simulation programs for selection with variable sizes of crosses and S(1) families within crosses. The breeding schemes and selection strategies showed similar relative efficiency for both optimization criteria DeltaG and P (0.1%). As compared with DHTC, S(1)TC-DHTC had larger DeltaG and P (0.1%), but a higher standard deviation of DeltaG. The superiority of S(1)TC-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 S(1) families. In DHTC, the best selection strategy was to ignore cross structures and use uniform size of crosses.

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 F(1) and F(2) 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 F(1) hybrid performance in the targeted mega-environment and F(1) 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 F(1) 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.

Efficiency gain of marker-assisted backcrossing by sequentially increasing marker densities over generations.

Expenses for marker assays are the major costs in marker-assisted backcrossing programs for the transfer of target genes from a donor into the genetic background of a recipient genotype. Our objectives were to (1) investigate the effect of employing sequentially increasing marker densities over backcross generations on the recurrent parent genome (RPG) recovery and the number of marker data points (MDP) required, and (2) determine optimum designs for attaining RPG thresholds of 93-98% with a minimum number of MDP. We simulated the introgression of one dominant target gene for genome models of sugar beet (Beta vulgaris L.) and maize (Zea mays L.) with varying marker distances of 5-80 cM and population sizes of 30-250 plants across BC(1) to BC(3) generations. Employing less dense maps in early backcross generations resulted in savings of over 50% in the number of required MDP compared with using a constant set of markers and was accompanied only by small reductions in the attained RPG values. The optimum designs were characterized by increasing marker densities and increasing population sizes in advanced generations for both genome models. We conclude that increasing simultaneously the marker density and the population size from early to advanced backcross generations results in gene introgression with a minimum number of required MDP.

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.