Multi-year linkage and association mapping confirm the high number of genomic regions involved in oilseed rape quantitative resistance to blackleg

Key message

A repertoire of the genomic regions involved in quantitative resistance to Leptosphaeria maculans in winter oilseed rape was established from combined linkage-based QTL and genome-wide association (GWA) mapping.

Abstract

Linkage-based mapping of quantitative trait loci (QTL) and genome-wide association studies are complementary approaches for deciphering the genomic architecture of complex agronomical traits. In oilseed rape, quantitative resistance to blackleg disease, caused by L. maculans, is highly polygenic and is greatly influenced by the environment. In this study, we took advantage of multi-year data available on three segregating populations derived from the resistant cv Darmor and multi-year data available on oilseed rape panels to obtain a wide overview of the genomic regions involved in quantitative resistance to this pathogen in oilseed rape. Sixteen QTL regions were common to at least two biparental populations, of which nine were the same as previously detected regions in a multi-parental design derived from different resistant parents. Eight regions were significantly associated with quantitative resistance, of which five on A06, A08, A09, C01 and C04 were located within QTL support intervals. Homoeologous Brassica napus genes were found in eight homoeologous QTL regions, which corresponded to 657 pairs of homoeologous genes. Potential candidate genes underlying this quantitative resistance were identified. Genomic predictions and breeding are also discussed, taking into account the highly polygenic nature of this resistance.

     

A major QTL on chromosome C05 significantly reduces acid detergent lignin (ADL) content and increases seed oil and protein content in oilseed rape (<Emphasis Type="Italic">Brassica napus</Emphasis> L.)

Key message

A reduction in acid detergent lignin content in oilseed rape resulted in an increase in seed oil and protein content.

Abstract

Worldwide increasing demand for vegetable oil and protein requires continuous breeding efforts to enhance the yield of oil and protein crop species. The oil-extracted meal of oilseed rape is currently mainly used for feeding livestock, but efforts are undertaken to use the oilseed rape protein in food production. One limiting factor is the high lignin content of black-seeded oilseed rape that negatively affects digestibility and sensory quality of food products compared to soybean. Breeding attempts to develop yellow seeded oilseed rape with reduced lignin content have not yet resulted in competitive cultivars. The objective of this work was to investigate the inheritance of seed quality in a DH population derived from the cross of the high oil lines SGDH14 and cv. Express. The DH population of 139 lines was tested in field experiments in 14 environments in north-west Europe. Seeds harvested from open pollinated plants were used for extensive seed quality analysis. A molecular marker map based on the Illumina Infinium 60 K Brassica SNP chip was used to map QTL. Amongst others, one major QTL for acid detergent lignin content, explaining 81% of the phenotypic variance, was identified on chromosome C05. Lines with reduced lignin content nevertheless did not show a yellowish appearance, but showed a reduced seed hull content. The position of the QTL co-located with QTL for oil and protein content of the defatted meal with opposite additive effects, suggesting that the reduction in lignin content resulted in an increase in oil and protein content.

     

The superior nitrogen efficiency of winter oilseed rape (Brassica napus L.) hybrids is not related to delayed nitrogen starvation-induced leaf senescence

Aims

Winter oilseed rape (Brassica napus L.) cultivation causes high nitrogen (N) balance surpluses. The breeding and cultivation of N-efficient cultivars (high grain yield under low N supply) can contribute to the reduction of the crop-specific N surpluses. Comparing line cultivars with hybrids and dwarfs the hypothesis was tested if stay-green into reproductive growth contributes to superior N efficiency of hybrids and dwarfs.

Methods

The present work comprised two years field experiments with ten line, five hybrid and three dwarf cultivars and hydroponic experiments with three hybrid and nine line cultivars.

Results

Hybrids were superior in yield formation independent of the N supply. The greater N efficiency of the hybrids was related to a higher N uptake until maturity, but not to stay-green. This was in agreement with a hydroponic experiment in which the hybrids were particularly responsive in N starvation-induced leaf senescence of older leaves as revealed by SPAD, photosynthesis and the expression of the senescence-specific cysteine protease gene SAG12-1. Additionally, hybrids were characterized by an efficient N retranslocation from vegetative to reproductive plant organs in combination with a lower grain-N concentration.

Conclusions

Both, N uptake and N utilization efficiency were decisive for the superior N efficiency of the hybrids.     

Phosphinothricin-resistant <Emphasis Type="Italic">Brassica napus</Emphasis> + <Emphasis Type="Italic">Orychophragmus violaceus</Emphasis> somatic hybrids

Hybrid plants resistant to phosphinothricin (PPT) are obtained as a result of experiments with somatic hybridization between Brassica napus L. cv. Kalinins’kyy and Orychophragmus violaceus L. O.E. Shulz. The hybrids inherited PPT resistance from O. violaceus plants that had been previously transformed by a vector containing the maize transposon system Spm/dSPm with bar gene located within the nonautonomous transposon. The morphologically obtained plants occupy an intermediate position between the initial forms, which is in agreement with the results of isoenzyme analyses (analysis of multiple forms of amylase and esterase) and PCR analysis (presence of the genes bar, gus, and SpmTPase). Inheritance of the plastome occurs from oilseed rape, while that of the mitochondrion, from O. violaceus, which is proved by means of PCR-RFLP analysis. The plant hybrids may be utilized for further selection research with oilseed rape following determination of the edible quality of its oil as well as in experiments with chloroplast transformation, a topic which is of critical importance for oilseed rape.     

Genomic models with genotype × environment interaction for predicting hybrid performance: an application in maize hybrids

Key message

A new genomic model that incorporates genotype?×?environment interaction gave increased prediction accuracy of untested hybrid response for traits such as percent starch content, percent dry matter content and silage yield of maize hybrids.

Abstract

The prediction of hybrid performance (HP) is very important in agricultural breeding programs. In plant breeding, multi-environment trials play an important role in the selection of important traits, such as stability across environments, grain yield and pest resistance. Environmental conditions modulate gene expression causing genotype?×?environment interaction (G?×?E), such that the estimated genetic correlations of the performance of individual lines across environments summarize the joint action of genes and environmental conditions. This article proposes a genomic statistical model that incorporates G?×?E for general and specific combining ability for predicting the performance of hybrids in environments. The proposed model can also be applied to any other hybrid species with distinct parental pools. In this study, we evaluated the predictive ability of two HP prediction models using a cross-validation approach applied in extensive maize hybrid data, comprising 2724 hybrids derived from 507 dent lines and 24 flint lines, which were evaluated for three traits in 58 environments over 12 years; analyses were performed for each year. On average, genomic models that include the interaction of general and specific combining ability with environments have greater predictive ability than genomic models without interaction with environments (ranging from 12 to 22%, depending on the trait). We concluded that including G?×?E in the prediction of untested maize hybrids increases the accuracy of genomic models.

     

Genomic prediction ability for yield-related traits in German winter barley elite material

Key message

Genomic prediction was evaluated in German winter barley breeding lines. In this material, prediction ability is strongly influenced by population structure and main determinant of prediction ability is the close genetic relatedness of the breeding material.

Abstract

To ensure breeding progress under changing environmental conditions the implementation and evaluation of new breeding methods is of crucial importance. Modern breeding approaches like genomic selection may significantly accelerate breeding progress. We assessed the potential of genomic prediction in a training population of 750 genotypes, consisting of multiple six-rowed winter barley (Hordeum vulgare L.) elite material families and old cultivars, which reflect the breeding history of barley in Germany. Crosses of parents selected from the training set were used to create a set of double-haploid families consisting of 750 genotypes. Those were used to confirm prediction ability estimates based on a cross-validation with the training set material using 11 different genomic prediction models. Population structure was inferred with dimensionality reduction methods like discriminant analysis of principle components and the influence of population structure on prediction ability was investigated. In addition to the size of the training set, marker density is of crucial importance for genomic prediction. We used genome-wide linkage disequilibrium and persistence of linkage phase as indicators to estimate that 11,203 evenly spaced markers are required to capture all QTL effects. Although a 9k SNP array does not contain a sufficient number of polymorphic markers for long-term genomic selection, we obtained fairly high prediction accuracies ranging from 0.31 to 0.71 for the traits earing, hectoliter weight, spikes per square meter, thousand kernel weight and yield and show that they result from the close genetic relatedness of the material. Our work contributes to designing long-term genetic prediction programs for barley breeding.

     

Validating the prediction accuracies of marker-assisted and genomic selection of Fusarium head blight resistance in wheat using an independent sample

Key message

Compared with independent validation, cross-validation simultaneously sampling genotypes and environments provided similar estimates of accuracy for genomic selection, but inflated estimates for marker-assisted selection.

Abstract

Estimates of prediction accuracy of marker-assisted (MAS) and genomic selection (GS) require validations. The main goal of our study was to compare the prediction accuracies of MAS and GS validated in an independent sample with results obtained from fivefold cross-validation using genomic and phenotypic data for Fusarium head blight resistance in wheat. In addition, the applicability of the reliability criterion, a concept originally developed in the context of classic animal breeding and GS, was explored for MAS. We observed that prediction accuracies of MAS were overestimated by 127% using cross-validation sampling genotype and environments in contrast to independent validation. In contrast, prediction accuracies of GS determined in independent samples are similar to those estimated with cross-validation sampling genotype and environments. This can be explained by small population differentiation between the training and validation sets in our study. For European wheat breeding, which is so far characterized by a slow temporal dynamic in allele frequencies, this assumption seems to be realistic. Thus, GS models used to improve European wheat populations are expected to possess a long-lasting validity. Since quantitative trait loci information can be exploited more precisely if the predicted genotype is more related to the training population, the reliability criterion is also a valuable tool to judge the level of prediction accuracy of individual genotypes in MAS.

     

Genomic prediction of starch content and chipping quality in tetraploid potato using genotyping-by-sequencing

Key message

Genomic prediction models for starch content and chipping quality show promising results, suggesting that genomic selection is a feasible breeding strategy in tetraploid potato.

Abstract

Genomic selection uses genome-wide molecular markers to predict performance of individuals and allows selections in the absence of direct phenotyping. It is regarded as a useful tool to accelerate genetic gain in breeding programs, and is becoming increasingly viable for crops as genotyping costs continue to fall. In this study, we have generated genomic prediction models for starch content and chipping quality in tetraploid potato to facilitate varietal development. Chipping quality was evaluated as the colour of a potato chip after frying following cold induced sweetening. We used genotyping-by-sequencing to genotype 762 offspring, derived from a population generated from biparental crosses of 18 tetraploid parents. Additionally, 74 breeding clones were genotyped, representing a test panel for model validation. We generated genomic prediction models from 171,859 single-nucleotide polymorphisms to calculate genomic estimated breeding values. Cross-validated prediction correlations of 0.56 and 0.73 were obtained within the training population for starch content and chipping quality, respectively, while correlations were lower when predicting performance in the test panel, at 0.30–0.31 and 0.42–0.43, respectively. Predictions in the test panel were slightly improved when including representatives from the test panel in the training population but worsened when preceded by marker selection. Our results suggest that genomic prediction is feasible, however, the extremely high allelic diversity of tetraploid potato necessitates large training populations to efficiently capture the genetic diversity of elite potato germplasm and enable accurate prediction across the entire spectrum of elite potatoes. Nonetheless, our results demonstrate that GS is a promising breeding strategy for tetraploid potato.

     

Increased genomic prediction accuracy in wheat breeding using a large Australian panel

Key message

Genomic prediction accuracy within a large panel was found to be substantially higher than that previously observed in smaller populations, and also higher than QTL-based prediction.

Abstract

In recent years, genomic selection for wheat breeding has been widely studied, but this has typically been restricted to population sizes under 1000 individuals. To assess its efficacy in germplasm representative of commercial breeding programmes, we used a panel of 10,375 Australian wheat breeding lines to investigate the accuracy of genomic prediction for grain yield, physical grain quality and other physiological traits. To achieve this, the complete panel was phenotyped in a dedicated field trial and genotyped using a custom Axiom^TM Affymetrix SNP array. A high-quality consensus map was also constructed, allowing the linkage disequilibrium present in the germplasm to be investigated. Using the complete SNP array, genomic prediction accuracies were found to be substantially higher than those previously observed in smaller populations and also more accurate compared to prediction approaches using a finite number of selected quantitative trait loci. Multi-trait genetic correlations were also assessed at an additive and residual genetic level, identifying a negative genetic correlation between grain yield and protein as well as a positive genetic correlation between grain size and test weight.

     

QTL analysis and the development of closely linked markers for days to flowering in spring oilseed rape (<Emphasis Type="Italic">Brassica napus</Emphasis> L.)

Days to flowering (DTF) is an important trait impacting cultivar performance in oilseed rape (Brassica napus L.), but the interaction of all loci controlling this trait in spring-type oilseed rape is not fully understood. We identified quantitative trait loci (QTL) for variation in DTF in a doubled haploid (DH) population from the Qinghai–Tibet Plateau that includes 217 lines derived from a cross between spring-type oilseed rape (B. napus L.) line No. 5246 and line No. 4512, the latter of which is responsive to the effective accumulated temperature (EAT). A linkage map was constructed for the DH population, using 202 SSR and 293 AFLP markers. At least 22 DTF QTL were found in multiple environments. Four major QTL were located on linkage groups A7, C2, C8 and C8. Among these QTL, cqDTFA7a and cqDTFC2a were identified in five environments and individually explained 10.4 and 23.0 % of the trait variation, respectively. cqDTFC8, a major QTL observed in spring environments, and a unique winter environment QTL, qDTFC8-3, were identified; these QTL explained 10.0 and 46.5 % of the phenotypic variation, respectively. Minor QTL (for example, cqDTFC2c) and epistatic interactions seemed evident in this population. Two closely linked SSR markers for cqDTFA7a and cqDTFC8 were developed (G1803 and S034). BnAP1, a B. napus gene with homology to Arabidopsis thaliana that was identified as a cqDTFA7a candidate gene, played a major role in this study. The allelic effects of the major and minor QTL on DTF were further validated in the DH population and in 93 breeding genotypes.     

Efficiency of multi-trait,indirect, and trait-assisted genomic selection for improvement of biomass sorghum

Key message

We compare genomic selection methods that use correlated traits to help predict biomass yield in sorghum, and find that trait-assisted genomic selection performs best.

Abstract

Genomic selection (GS) is usually performed on a single trait, but correlated traits can also help predict a focal trait through indirect or multi-trait GS. In this study, we use a pre-breeding population of biomass sorghum to compare strategies that use correlated traits to improve prediction of biomass yield, the focal trait. Correlated traits include moisture, plant height measured at monthly intervals between planting and harvest, and the area under the growth progress curve. In addition to single- and multi-trait direct and indirect GS, we test a new strategy called trait-assisted GS, in which correlated traits are used along with marker data in the validation population to predict a focal trait. Single-trait GS for biomass yield had a prediction accuracy of 0.40. Indirect GS performed best using area under the growth progress curve to predict biomass yield, with a prediction accuracy of 0.37, and did not differ from indirect multi-trait GS that also used moisture information. Multi-trait GS and single-trait GS yielded similar results, indicating that correlated traits did not improve prediction of biomass yield in a standard GS scenario. However, trait-assisted GS increased prediction accuracy by up to \(50\%\) when using plant height in both the training and validation populations to help predict yield in the validation population. Coincidence between selected genotypes in phenotypic and genomic selection was also highest in trait-assisted GS. Overall, these results suggest that trait-assisted GS can be an efficient strategy when correlated traits are obtained earlier or more inexpensively than a focal trait.

     

Development of crop-specific transposable element (SINE) markers for studying gene flow from oilseed rape to wild radish

The screening of wild populations for evidence of gene flow from a crop to a wild related species requires the unambiguous detection of crop genes within the genome of the wild species, taking into account the intraspecific variability of each species. If the crop and wild relatives share a common ancestor, as is the case for the Brassica crops and their wild relatives (subtribe Brassiceae), the species-specific markers needed to make this unambiguous detection are difficult to identify. In the model oilseed rape (Brassica napus, AACC, 2n=38)-wild radish (Raphanus raphanistrum, RrRr, 2n=18) system, we utilized the presence or absence of a short-interspersed element (SINE) at a given locus to develop oilseed rape-specific markers, as SINE insertions are irreversible. By means of sequence-specific amplified polymorphism (SINE-SSAP) reactions, we identified and cloned 67 bands specific to the oilseed rape genome and absent from that of wild radish. Forty-seven PCR-specific markers were developed from three combinations of primers anchored either in (1) the 5- and 3-genomic sequences flanking the SINE, (2) the 5-flanking and SINE internal sequences or (3) the SINE internal and flanking 3-sequences. Seventeen markers were monomorphic whatever the oilseed rape varieties tested, whereas 30 revealed polymorphism and behaved either as dominant (17) or co-dominant (13) markers. Polymorphic markers were mapped on 19 genomic regions assigned to ten linkage groups. The markers developed will be efficient tools to trace the occurrence and frequency of introgressions of oilseed rape genomic region within wild radish populations.     

Molecular and cytological analyses of A and C genomes at meiosis in synthetic allotriploid <Emphasis Type="Italic">Brassica</Emphasis> hybrids (ACC) between <Emphasis Type="Italic">B.napus</Emphasis> (AACC) and <Emphasis Type="Italic">B.oleracea</Emphasis> (CC)

Success of interspecific hybridization relies mostly on the adequate similarity between the implicated genomes to ensure synapsis, pairing and recombination between appropriate chromosomes during meiosis in allopolyploid species. Allotetraploid Brassica napus (AACC) is a model of natural hybridization between Brassica rapa (AA) and Brassica oleracea (CC), which are originally derived from a common ancestor, but genomic constitution of the same chromosomes probably varied among these species through time after establishment, giving rise to cytogenetic difference in the synthetic hybrids. Herein we investigated meiotic behaviors of A and C chromosomes of synthetic allotriploid Brassica hybrids (ACC) at molecular and cytological levels, which result from the interspecific cross between natural B. napus (AACC) and B.oleracea (CC), and the results showed that meiosis course was significantly aberrant in allotriploid Brassica hybrids, and chromosomes aligned chaotically at metaphase I, chromosome bridges and lags were frequently observed from later metaphase I to anaphase II during meiosis. Simultaneously, we also noticed that meiosis-related genes were abruptly down-regulated in allotriploid Brassica hybrids, which likely accounted for irregular scenario of meiosis observed in these synthetic hybrids. Therefore, these results indicated that inter-genomic exchanges of A and C chromosomes could occur frequently in synthetic Brassica hybrids, and provided an efficient approach for genetic changes of homeologous chromosomes during meiosis in polyploid B.napus breeding program.     

Advantages and limitations of multiple-trait genomic prediction for <Emphasis Type="Italic">Fusarium</Emphasis> head blight severity in hybrid wheat (<Emphasis Type="Italic">Triticum aestivum</Emphasis> L.)

Key message

Predictabilities for wheat hybrids less related to the estimation set were improved by shifting from single- to multiple-trait genomic prediction of Fusarium head blight severity.

Abstract

Breeding for improved Fusarium head blight resistance (FHBr) of wheat is a very laborious and expensive task. FHBr complexity is mainly due to its highly polygenic nature and because FHB severity (FHBs) is greatly influenced by the environment. Associated traits plant height and heading date may provide additional information related to FHBr, but this is ignored in single-trait genomic prediction (STGP). The aim of our study was to explore the benefits in predictabilities of multiple-trait genomic prediction (MTGP) over STGP of target trait FHBs in a population of 1604 wheat hybrids using information on 17,372 single nucleotide polymorphism markers along with indicator traits plant height and heading date. The additive inheritance of FHBs allowed accurate hybrid performance predictions using information on general combining abilities or average performance of both parents without the need of markers. Information on molecular markers and indicator trait(s) improved FHBs predictabilities for hybrids less related to the estimation set. Indicator traits must be observed on the predicted individuals to benefit from MTGP. Magnitudes of genetic and phenotypic correlations along with improvements in predictabilities made plant height a better indicator trait for FHBs than heading date. Thus, MTGP having only plant height as indicator trait already maximized FHBs predictabilities. Provided a good indicator trait was available, MTGP could reduce the impacts of genotype environment \(\times\) interaction on STGP for hybrids less related to the estimation set.

     

Root growth in biopores—evaluation with in situ endoscopy

Background and aims

The significance of biopores for nutrient acquisition from the subsoil depends on root-soil contact, which in turn is influenced by root architecture. The aim of this study was to detect differences regarding the architecture and root-soil contact of homorhizous barley roots (Hordeum vulgare L.) and allorhizous oilseed rape roots (Brassica napus L.) growing in biopores.

Methods

In situ endoscopy was used as a technique that allows non-destructive display of pore wall characteristics and root morphology inside large biopores under field conditions.

Results

For both crops, about 85 % of all roots did establish contact to the pore wall. However, according to their different root architecture, the two crops varied in their strategy of resource acquisition: While barley was characterized by thin vertical or ingrowing roots, most of them in direct contact to the pore wall, oilseed rape established contact to the pore wall predominantly via lateral roots.

Conclusions

Root morphological and pore wall assessment with in situ endoscopy in combination with detailed studies of soil biochemical and soil physical parameters of the pore wall is considered an essential prerequisite for more precise future modelling of nutrient acquisition and uptake.     

Seed colour loci, homoeology and linkage groups of the C genome chromosomes revealed in Brassica rapa-B. oleracea monosomic alien addition lines

Background and Aims

Brassica rapa and B. oleracea are the progenitors of oilseed rape B. napus. The addition of each chromosome of B. oleracea to the chromosome complement of B. rapa results in a series of monosomic alien addition lines (MAALs). Analysis of MAALs determines which B. oleracea chromosomes carry genes controlling specific phenotypic traits, such as seed colour. Yellow-seeded oilseed rape is a desirable breeding goal both for food and livestock feed end-uses that relate to oil, protein and fibre contents. The aims of this study included developing a missing MAAL to complement an available series, for studies on seed colour control, chromosome homoeology and assignment of linkage groups to B. oleracea chromosomes.

Methods

A new batch of B. rapa–B. oleracea aneuploids was produced to generate the missing MAAL. Seed colour and other plant morphological features relevant to differentiation of MAALs were recorded. For chromosome characterization, Snow''s carmine, fluorescence in situ hybridization (FISH) and genomic in situ hybridization (GISH) were used.

Key Results

The final MAAL was developed. Morphological traits that differentiated the MAALs comprised cotyledon number, leaf morphology, flower colour and seed colour. Seed colour was controlled by major genes on two B. oleracea chromosomes and minor genes on five other chromosomes of this species. Homoeologous pairing was largely between chromosomes with similar centromeric positions. FISH, GISH and a parallel microsatellite marker analysis defined the chromosomes in terms of their linkage groups.

Conclusions

A complete set of MAALs is now available for genetic, genomic, evolutionary and breeding perspectives. Defining chromosomes that carry specific genes, physical localization of DNA markers and access to established genetic linkage maps contribute to the integration of these approaches, manifested in the confirmed correspondence of linkage groups with specific chromosomes. Applications include marker-assisted selection and breeding for yellow seeds.     

Response and inbreeding from a genomic selection experiment in layer chickens

Background

Genomic selection (GS) using estimated breeding values (GS-EBV) based on dense marker data is a promising approach for genetic improvement. A simulation study was undertaken to illustrate the opportunities offered by GS for designing breeding programs. It consisted of a selection program for a sex-limited trait in layer chickens, which was developed by deterministic predictions under different scenarios. Later, one of the possible schemes was implemented in a real population of layer chicken.

Methods

In the simulation, the aim was to double the response to selection per year by reducing the generation interval by 50 %, while maintaining the same rate of inbreeding per year. We found that GS with retraining could achieve the set objectives while requiring 75 % fewer reared birds and 82 % fewer phenotyped birds per year. A multi-trait GS scenario was subsequently implemented in a real population of brown egg laying hens. The population was split into two sub-lines, one was submitted to conventional phenotypic selection, and one was selected based on genomic prediction. At the end of the 3-year experiment, the two sub-lines were compared for multiple performance traits that are relevant for commercial egg production.

Results

Birds that were selected based on genomic prediction outperformed those that were submitted to conventional selection for most of the 16 traits that were included in the index used for selection. However, although the two programs were designed to achieve the same rate of inbreeding per year, the realized inbreeding per year assessed from pedigree was higher in the genomic selected line than in the conventionally selected line.

Conclusions

The results demonstrate that GS is a promising alternative to conventional breeding for genetic improvement of layer chickens.