Unraveling the potential of phenomic selection within and among diverse breeding material of maize (Zea mays L.).

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.

High-resolution association mapping with libraries of immortalized lines from ancestral landraces.

KEY MESSAGE: Association mapping with immortalized lines of landraces offers several advantages including a high mapping resolution, as demonstrated here in maize by identifying the causal variants underlying QTL for oil content and the metabolite allantoin. Landraces are traditional varieties of crops that present a valuable yet largely untapped reservoir of genetic variation to meet future challenges of agriculture. Here, we performed association mapping in a panel comprising 358 immortalized maize lines from six European Flint landraces. Linkage disequilibrium decayed much faster in the landraces than in the elite lines included for comparison, permitting a high mapping resolution. We demonstrate this by fine-mapping a quantitative trait locus (QTL) for oil content down to the phenylalanine insertion F469 in DGAT1-2 as the causal variant. For the metabolite allantoin, related to abiotic stress response, we identified promoter polymorphisms and differential expression of an allantoinase as putative cause of variation. Our results demonstrate the power of this approach to dissect QTL potentially down to the causal variants, toward the utilization of natural or engineered alleles in breeding. Moreover, we provide guidelines for studies using ancestral landraces for crop genetic research and breeding.

Can we abandon phosphorus starter fertilizer in maize? Results from a diverse panel of elite and doubled haploid landrace lines of maize (Zea mays L.).

The importance of phosphorus (P) in agriculture contrasts with the negative environmental impact and the limited resources worldwide. Reducing P fertilizer application by utilizing more efficient genotypes is a promising way to address these issues. To approach this, a large panel of maize (Zea mays L.) comprising each 100 Flint and Dent elite lines and 199 doubled haploid lines from six landraces was assessed in multi-environment field trials with and without the application of P starter fertilizer. The treatment comparison showed that omitting the starter fertilizer can significantly affect traits in early plant development but had no effect on grain yield. Young maize plants provided with additional P showed an increased biomass, faster growth and superior vigor, which, however, was only the case under environmental conditions considered stressful for maize cultivation. Importantly, though the genotype-by-treatment interaction variance was comparably small, there is genotypic variation for this response that can be utilized in breeding. The comparison of elite and doubled haploid landrace lines revealed a superior agronomic performance of elite material but also potentially valuable variation for early traits in the landrace doubled haploid lines. In conclusion, our results illustrate that breeding for P efficient maize cultivars is possible towards a reduction of P fertilizer in a more sustainable agriculture.

Haploid male fertility and spontaneous chromosome doubling evaluated in a diallel and recurrent selection experiment in maize.

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. https://doi.org/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.

Testcross performance of doubled haploid lines from European flint maize landraces is promising for broadening the genetic base of elite germplasm.

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.

Across-years prediction of hybrid performance in maize using genomics.

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.

Beyond Genomic Prediction: Combining Different Types of omics Data Can Improve Prediction of Hybrid Performance in Maize.

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.

Omics-based hybrid prediction in maize.

KEY MESSAGE: Complementing genomic data with other "omics" predictors can increase the probability of success for predicting the best hybrid combinations using complex agronomic traits. Accurate prediction of traits with complex genetic architecture is crucial for selecting superior candidates in animal and plant breeding and for guiding decisions in personalized medicine. Whole-genome prediction has revolutionized these areas but has inherent limitations in incorporating intricate epistatic interactions. Downstream "omics" data are expected to integrate interactions within and between different biological strata and provide the opportunity to improve trait prediction. Yet, predicting traits from parents to progeny has not been addressed by a combination of "omics" data. Here, we evaluate several "omics" predictors-genomic, transcriptomic and metabolic data-measured on parent lines at early developmental stages and demonstrate that the integration of transcriptomic with genomic data leads to higher success rates in the correct prediction of untested hybrid combinations in maize. Despite the high predictive ability of genomic data, transcriptomic data alone outperformed them and other predictors for the most complex heterotic trait, dry matter yield. An eQTL analysis revealed that transcriptomic data integrate genomic information from both, adjacent and distant sites relative to the expressed genes. Together, these findings suggest that downstream predictors capture physiological epistasis that is transmitted from parents to their hybrid offspring. We conclude that the use of downstream "omics" data in prediction can exploit important information beyond structural genomics for leveraging the efficiency of hybrid breeding.

Safeguarding Our Genetic Resources with Libraries of Doubled-Haploid Lines.

Thousands of landraces are stored in seed banks as "gold reserves" for future use in plant breeding. In many crops, their utilization is hampered because they represent heterogeneous populations of heterozygous genotypes, which harbor a high genetic load. We show, with high-density genotyping in five landraces of maize, that libraries of doubled-haploid (DH) lines capture the allelic diversity of genetic resources in an unbiased way. By comparing allelic differentiation between heterozygous plants from the original landraces and 266 derived DH lines, we find conclusive evidence that, in the DH production process, sampling of alleles is random across the entire allele frequency spectrum, and purging of landraces from their genetic load does not act on specific genomic regions. Based on overall process efficiency, we show that generating DH lines is feasible for genetic material that has never been selected for inbreeding tolerance. We conclude that libraries of DH lines will make genetic resources accessible to crop improvement by linking molecular inventories of seed banks with meaningful phenotypes.

Tapping the genetic diversity of landraces in allogamous crops with doubled haploid lines: a case study from European flint maize.

KEY MESSAGE: Using landraces for broadening the genetic base of elite maize germplasm is hampered by heterogeneity and high genetic load. Production of DH line libraries can help to overcome these problems. Landraces of maize (Zea mays L.) represent a huge reservoir of genetic diversity largely untapped by breeders. Genetic heterogeneity and a high genetic load hamper their use in hybrid breeding. Production of doubled haploid line libraries (DHL) by the in vivo haploid induction method promises to overcome these problems. To test this hypothesis, we compared the line per se performance of 389 doubled haploid (DH) lines across six DHL produced from European flint landraces with that of four flint founder lines (FFL) and 53 elite flint lines (EFL) for 16 agronomic traits evaluated in four locations. The genotypic variance ([Formula: see text]) within DHL was generally much larger than that among DHL and exceeded also [Formula: see text] of the EFL. For most traits, the means and [Formula: see text] differed considerably among the DHL, resulting in different expected selection gains. Mean grain yield of the EFL was 25 and 62% higher than for the FFL and DHL, respectively, indicating considerable breeding progress in the EFL and a remnant genetic load in the DHL. Usefulness of the best 20% lines was for individual DHL comparable to the EFL and grain yield (GY) in the top lines from both groups was similar. Our results corroborate the tremendous potential of landraces for broadening the narrow genetic base of elite germplasm. To make best use of these "gold reserves", we propose a multi-stage selection approach with optimal allocation of resources to (1) choose the most promising landraces for DHL production and (2) identify the top DH lines for further breeding.

Low validation rate of quantitative trait loci for Gibberella ear rot resistance in European maize.

KEY MESSAGE: Six quantitative trait loci (QTL) for Gibberella ear rot resistance in maize were tested in two different genetic backgrounds; three QTL displayed an effect in few near isogenic line pairs. Few quantitative trait loci (QTL) mapping studies for Gibberella ear rot (GER) have been conducted, but no QTL have been verified so far. QTL validation is prudent before their implementation into marker-assisted selection (MAS) programs. Our objectives were to (1) validate six QTL for GER resistance, (2) evaluate the QTL across two genetic backgrounds, (3) investigate the genetic background outside the targeted introgressions. Pairs of near isogenic lines (NILs) segregating for a single QTL (Qger1, Qger2, Qger10, Qger13, Qger16, or Qger21) were developed by recurrent backcross until generation BC3S2. Donor parents (DP) carrying QTL were backcrossed to a susceptible (UH009) and a moderately resistant (UH007) recurrent parent. MAS was performed using five SNP markers covering a region of 40 cM around each QTL. All NILs were genotyped with the MaizeSNP50 assay and phenotyped for GER severity and deoxynivalenol and zearalenone content. Traits were significantly (P < 0.001) intercorrelated. Out of 34 NIL pairs with the UH009 genetic background, three pairs showed significant differences in at least one trait for three QTL (Qger1, Qger2, Qger13). Out of 25 NIL pairs with the UH007 genetic background, five pairs showed significant differences in at least one trait for two QTL (Qger2, Qger21). However, Qger16, Qger10 and Qger13 were most likely false positives. The genetic background possibly affected NIL pairs comparisons due to linkage drag and/or epistasis with residual loci from the DP in non-target regions. In conclusion, validation rates were disappointingly low, which further indicates that GER resistance is controlled by many low-effect QTL.

Variation in ruminal in situ degradation of crude protein and starch from maize grains compared to in vitro gas production kinetics and physical and chemical characteristics.

The objectives of this study were (1) to evaluate in situ ruminal dry matter (DM), crude protein (CP) and starch degradation characteristics and in vitro gas production (GP) kinetics using a set of 20 different maize grain genotypes and (2) to predict the effective degradation (ED) of CP and starch from chemical and physical characteristics alone or in combination with in vitro GP measurements. Maize grains were characterised by different chemical and physical characteristics. Ruminal in situ degradation was measured in three lactating Jersey cows. Ground grains (sieve size: 2 mm) were incubated in bags for 1, 2, 4, 8, 16, 24, 48 and 72 h. Bag residues were analysed for CP and starch content. Degradation kinetics was determined and the ED of DM, CP and starch calculated using a ruminal passage rate of 5%/h and 8%/h. The GP of the grains (sieve size: 1 mm) was recorded after 2, 4, 6, 8, 12, 24, 48 and 72 h incubation in buffered rumen fluid and fitted to an exponential equation to determine GP kinetics. Correlations and stepwise multiple linear regressions were evaluated for the prediction of ED calculated for a passage rate of 5%/h (ED5) for CP (EDCP5) and starch (EDST5). The in situ parameters and ED5 varied widely between genotypes with average values (±SD) of 64% ± 4.2, 62% ± 4.1 and 65% ± 5.2 for ED5 of DM, EDCP5 and EDST5 and were on average 10 percentage points lower for a passage rate of 8%/h. Degradation rates varied between 4.8%/h and 7.4%/h, 4.1%/h and 6.5%/h and 5.3%/h and 8.9%/h for DM, CP and starch, respectively. These rates were in the same range as GP rates (6.0-8.3%/h). The EDCP5 and EDST5 were related to CP concentration and could be evaluated in detail using CP fractions and specific amino acids. In vitro GP measurements and GP rates correlated well with EDCP5 and EDST5 and predicted EDCP5 and EDST5 in combination with the chemical characteristics of the samples. Equations can be used to obtain quick and cost effective information on ruminal degradation of CP and starch from maize grains.

Variation in chemical composition and physical characteristics of cereal grains from different genotypes.

Genotypes of cereal grains, including winter barley (n = 21), maize (n = 27), oats (n = 14), winter rye (n = 22), winter triticale (n = 21) and winter wheat (n = 29), were assayed for their chemical composition and physical characteristics as part of the collaborative research project referred to as GrainUp. Genotypes of one grain species were grown on the same site, except maize. In general, concentrations of proximate nutrients were not largely different from feed tables. The coefficient of variation (CV) for the ether extract concentration of maize was high because the data pool comprised speciality maize bred for its high oil content. A subset of 8 barley, 20 rye, 20 triticale and 20 wheat samples was analysed to differ significantly in several carbohydrate fractions. Gross energy concentration of cereal grains could be predicted from proximate nutrient concentration with good accuracy. The mean lysine concentration of protein was the highest in oats (4.2 g/16 g N) and the lowest in wheat (2.7 g/16 g N). Significant differences were also detected in the concentrations of macro elements as well as iron, manganese, zinc and copper. Concentrations of arsenic, cadmium and lead were below the limit of detection. The concentration of lower inositol phosphates was low, but some inositol pentaphosphates were detected in all grains. In barley, relatively high inositol tetraphosphate concentration also was found. Intrinsic phytase activity was the highest in rye, followed by triticale, wheat, barley and maize, and it was not detectable in oats. Substantial differences were seen in the thousand seed weight, test weight, falling number and extract viscoelasticity characteristics. The study is a comprehensive overview of the composition of different cereal grain genotypes when grown on the same location. The relevance of the variation in composition for digestibility in different animal species will be subject of other communications.

The Genetic Basis of Haploid Induction in Maize Identified with a Novel Genome-Wide Association Method.

In vivo haploid induction (HI) triggered by pollination with special intraspecific genotypes, called inducers, is unique to Zea maysL. 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.

Linkage disequilibrium with linkage analysis of multiline crosses reveals different multiallelic QTL for hybrid performance in the flint and dent heterotic groups of maize.

Multiparental designs combined with dense genotyping of parents have been proposed as a way to increase the diversity and resolution of quantitative trait loci (QTL) mapping studies, using methods combining linkage disequilibrium information with linkage analysis (LDLA). Two new nested association mapping designs adapted to European conditions were derived from the complementary dent and flint heterotic groups of maize (Zea mays L.). Ten biparental dent families (N = 841) and 11 biparental flint families (N = 811) were genotyped with 56,110 single nucleotide polymorphism markers and evaluated as test crosses with the central line of the reciprocal design for biomass yield, plant height, and precocity. Alleles at candidate QTL were defined as (i) parental alleles, (ii) haplotypic identity by descent, and (iii) single-marker groupings. Between five and 16 QTL were detected depending on the model, trait, and genetic group considered. In the flint design, a major QTL (R(2) = 27%) with pleiotropic effects was detected on chromosome 10, whereas other QTL displayed milder effects (R(2) < 10%). On average, the LDLA models detected more QTL but generally explained lower percentages of variance, consistent with the fact that most QTL display complex allelic series. Only 15% of the QTL were common to the two designs. A joint analysis of the two designs detected between 15 and 21 QTL for the five traits. Of these, between 27 for silking date and 41% for tasseling date were significant in both groups. Favorable allelic effects detected in both groups open perspectives for improving biomass production.

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.

Genome properties and prospects of genomic prediction of hybrid performance in a breeding program of maize.

Maize (Zea mays L.) serves as model plant for heterosis research and is the crop where hybrid breeding was pioneered. We analyzed genomic and phenotypic data of 1254 hybrids of a typical maize hybrid breeding program based on the important Dent × Flint heterotic pattern. Our main objectives were to investigate genome properties of the parental lines (e.g., allele frequencies, linkage disequilibrium, and phases) and examine the prospects of genomic prediction of hybrid performance. We found high consistency of linkage phases and large differences in allele frequencies between the Dent and Flint heterotic groups in pericentromeric regions. These results can be explained by the Hill-Robertson effect and support the hypothesis of differential fixation of alleles due to pseudo-overdominance in these regions. In pericentromeric regions we also found indications for consistent marker-QTL linkage between heterotic groups. With prediction methods GBLUP and BayesB, the cross-validation prediction accuracy ranged from 0.75 to 0.92 for grain yield and from 0.59 to 0.95 for grain moisture. The prediction accuracy of untested hybrids was highest, if both parents were parents of other hybrids in the training set, and lowest, if none of them were involved in any training set hybrid. Optimizing the composition of the training set in terms of number of lines and hybrids per line could further increase prediction accuracy. We conclude that genomic prediction facilitates a paradigm shift in hybrid breeding by focusing on the performance of experimental hybrids rather than the performance of parental lines in test crosses.

Intraspecific variation of recombination rate in maize.

BACKGROUND: In sexually reproducing organisms, meiotic crossovers ensure the proper segregation of chromosomes and contribute to genetic diversity by shuffling allelic combinations. Such genetic reassortment is exploited in breeding to combine favorable alleles, and in genetic research to identify genetic factors underlying traits of interest via linkage or association-based approaches. Crossover numbers and distributions along chromosomes vary between species, but little is known about their intraspecies variation. RESULTS: Here, we report on the variation of recombination rates between 22 European maize inbred lines that belong to the Dent and Flint gene pools. We genotype 23 doubled-haploid populations derived from crosses between these lines with a 50 k-SNP array and construct high-density genetic maps, showing good correspondence with the maize B73 genome sequence assembly. By aligning each genetic map to the B73 sequence, we obtain the recombination rates along chromosomes specific to each population. We identify significant differences in recombination rates at the genome-wide, chromosome, and intrachromosomal levels between populations, as well as significant variation for genome-wide recombination rates among maize lines. Crossover interference analysis using a two-pathway modeling framework reveals a negative association between re combination rate and interference strength. CONCLUSIONS: To our knowledge, the present work provides the most comprehensive study on intraspecific variation of recombination rates and crossover interference strength in eukaryotes. Differences found in recombination rates will allow for selection of high or low recombining lines in crossing programs. Our methodology should pave the way for precise identification of genes controlling recombination rates in maize and other organisms.

Rapid and accurate identification of in vivo-induced haploid seeds based on oil content in maize.

The needs of a growing human population require rapid and efficient development of improved cultivars by plant breeders. The doubled haploid (DH) technology enables generating completely homozygous lines in a single step and, thus, is central to modern genetics and breeding approaches. Rapid and reliable identification of seeds with a haploid embryo after in vivo haploid induction is elementary in the method utilized in maize but current systems have severe shortcomings preventing their use in many germplasm types. Here, we describe an alternative method for discrimination of haploid from diploid seeds based on differences in their oil content stemming from pollination with high oil inducers. After presenting some fundamental theory, we provide a proof-of-concept with experimental results, demonstrating acceptable error rates across different germplasm. Our approach represents a breakthrough in DH technology in maize, because it is amenable to automated high-throughput screening and applicable to any maize germplasm worldwide.

Unlocking the genetic diversity of maize landraces with doubled haploids opens new avenues for breeding.

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.