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

Understanding genetic diversity in drought-adaptive hybrid parental lines in pearl millet

Information on genetic diversity and population structure is helpful to strategize enhancing the genetic base of hybrid parental lines in breeding programs. The present study determined the population structure and genetic diversity of 109 pearl millet hybrid parental lines, known for their better adaptation and performance in drought-prone environments, using 16,472 single nucleotide polymorphic (SNP) markers generated from GBS (genotyping-by-sequencing) platforms. The SNPs were distributed uniformly across the pearl millet genome and showed considerable genetic diversity (0.337), expected heterozygosity (0.334), and observed heterozygosity (0.031). Most of the pairs of lines (78.36%) had Identity-by-State (IBS) based genetic distances of more than 0.3, indicating a significant amount of genetic diversity among the parental lines. Bayesian model-based population stratification, neighbor-joining phylogenetic analysis, and principal coordinate analysis (PCoA) differentiated all hybrid parental lines into two clear-cut major groups, one each for seed parents (B-lines) and pollinators (R-lines). Majority of parental lines sharing common parentages were found grouped in the same cluster. Analysis of molecular variance (AMOVA) revealed 7% of the variation among subpopulations, and 93% of the variation was attributable to within sub-populations. Chromosome 3 had the highest number of LD regions. Genomic LD decay distance was 0.69 Mb and varied across the different chromosomes. Genetic diversity based on 11 agro-morphological and grain quality traits also suggested that the majority of the B- and R-lines were grouped into two major clusters with few overlaps. In addition, the combined analysis of phenotypic and genotypic data showed similarities in the population grouping patterns. The present study revealed the uniqueness of most of the inbred lines, which can be a valuable source of new alleles and help breeders to utilize these inbred lines for the development of hybrids in drought-prone environments.

Selection signature analyses and genome-wide association reveal genomic hotspot regions that reflect differences between breeds of horse with contrasting risk of degenerative suspensory ligament desmitis

Degenerative suspensory ligament desmitis is a progressive idiopathic condition that leads to scarring and rupture of suspensory ligament fibers in multiple limbs in horses. The prevalence of degenerative suspensory ligament desmitis is breed related. Risk is high in the Peruvian Horse, whereas pony and draft breeds have low breed risk. Degenerative suspensory ligament desmitis occurs in families of Peruvian Horses, but its genetic architecture has not been definitively determined. We investigated contrasts between breeds with differing risk of degenerative suspensory ligament desmitis and identified associated risk variants and candidate genes. We analyzed 670k single nucleotide polymorphisms from 10 breeds, each of which was assigned one of the four breed degenerative suspensory ligament desmitis risk categories: control (Belgian, Icelandic Horse, Shetland Pony, and Welsh Pony), low risk (Lusitano, Arabian), medium risk (Standardbred, Thoroughbred, Quarter Horse), and high risk (Peruvian Horse). Single nucleotide polymorphisms were used for genome-wide association and selection signature analysis using breed-assigned risk levels. We found that the Peruvian Horse is a population with low effective population size and our breed contrasts suggest that degenerative suspensory ligament desmitis is a polygenic disease. Variant frequency exhibited signatures of positive selection across degenerative suspensory ligament desmitis breed risk groups on chromosomes 7, 18, and 23. Our results suggest degenerative suspensory ligament desmitis breed risk is associated with disturbances to suspensory ligament homeostasis where matrix responses to mechanical loading are perturbed through disturbances to aging in tendon (PIN1), mechanotransduction (KANK1, KANK2, JUNB, SEMA7A), collagen synthesis (COL4A1, COL5A2, COL5A3, COL6A5), matrix responses to hypoxia (PRDX2), lipid metabolism (LDLR, VLDLR), and BMP signaling (GREM2). Our results do not suggest that suspensory ligament proteoglycan turnover is a primary factor in disease pathogenesis.

Building a Calibration Set for Genomic Prediction, Characteristics to Be Considered, and Optimization Approaches

The efficiency of genomic selection strongly depends on the prediction accuracy of the genetic merit of candidates. Numerous papers have shown that the composition of the calibration set is a key contributor to prediction accuracy. A poorly defined calibration set can result in low accuracies, whereas an optimized one can considerably increase accuracy compared to random sampling, for a same size. Alternatively, optimizing the calibration set can be a way of decreasing the costs of phenotyping by enabling similar levels of accuracy compared to random sampling but with fewer phenotypic units. We present here the different factors that have to be considered when designing a calibration set, and review the different criteria proposed in the literature. We classified these criteria into two groups: model-free criteria based on relatedness, and criteria derived from the linear mixed model. We introduce criteria targeting specific prediction objectives including the prediction of highly diverse panels, biparental families, or hybrids. We also review different ways of updating the calibration set, and different procedures for optimizing phenotyping experimental designs.

SoySNP618K array: A high-resolution single nucleotide polymorphism platform as a valuable genomic resource for soybean genetics and breeding

Innovations in genomics have enabled the development of low-cost, high-resolution, single nucleotide polymorphism (SNP) genotyping arrays that accelerate breeding progress and support basic research in crop science. Here, we developed and validated the SoySNP618K array (618,888 SNPs) for the important crop soybean. The SNPs were selected from whole-genome resequencing data containing 2,214 diverse soybean accessions; 29.34% of the SNPs mapped to genic regions representing 86.85% of the 56,044 annotated high-confidence genes. Identity-by-state analyses of 318 soybeans revealed 17 redundant accessions, highlighting the potential of the SoySNP618K array in supporting gene bank management. The patterns of population stratification and genomic regions enriched through domestication were highly consistent with previous findings based on resequencing data, suggesting that the ascertainment bias in the SoySNP618K array was largely compensated for. Genome-wide association mapping in combination with reported quantitative trait loci enabled fine-mapping of genes known to influence flowering time, E2 and GmPRR3b, and of a new candidate gene, GmVIP5. Moreover, genomic prediction of flowering and maturity time in 502 recombinant inbred lines was highly accurate (>0.65). Thus, the SoySNP618K array is a valuable genomic tool that can be used to address many questions in applied breeding, germplasm management, and basic crop research.

Phenotypic and molecular characterization of a set of tropical maize inbred lines from a public breeding program in Brazil

Background

The characterization of genetic diversity and population differentiation for maize inbred lines from breeding programs is of great value in assisting breeders in maintaining and potentially increasing the rate of genetic gain. In our study, we characterized a set of 187 tropical maize inbred lines from the public breeding program of the Universidade Federal de Viçosa (UFV) in Brazil based on 18 agronomic traits and 3,083 single nucleotide polymorphisms (SNP) markers to evaluate whether this set of inbred lines represents a panel of tropical maize inbred lines for association mapping analysis and investigate the population structure and patterns of relationships among the inbred lines from UFV for better exploitation in our maize breeding program.

Results

Our results showed that there was large phenotypic and genotypic variation in the set of tropical maize inbred lines from the UFV maize breeding program. We also found high genetic diversity (GD = 0.34) and low pairwise kinship coefficients among the maize inbred lines (only approximately 4.00 % of the pairwise relative kinship was above 0.50) in the set of inbred lines. The LD decay distance over all ten chromosomes in the entire set of maize lines with r² = 0.1 was 276,237 kb. Concerning the population structure, our results from the model-based STRUCTURE and principal component analysis methods distinguished the inbred lines into three subpopulations, with high consistency maintained between both results. Additionally, the clustering analysis based on phenotypic and molecular data grouped the inbred lines into 14 and 22 genetic divergence clusters, respectively.

Conclusions

Our results indicate that the set of tropical maize inbred lines from UFV maize breeding programs can comprise a panel of tropical maize inbred lines suitable for a genome-wide association study to dissect the variation of complex quantitative traits in maize, mainly in tropical environments. In addition, our results will be very useful for assisting us in the assignment of heterotic groups and the selection of the best parental combinations for new breeding crosses, mapping populations, mapping synthetic populations, guiding crosses that target highly heterotic and yielding hybrids, and predicting untested hybrids in the public breeding program UFV.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-08127-7.

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

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.

Population genomics of Mediterranean oat (A. sativa) reveals high genetic diversity and three loci for heading date

Genomic analysis of Mediterranean oats reveals high genetic diversity and three loci for adaptation to this environment. This information together with phenotyping and passport data, gathered in an interactive map, will be a vital resource for oat genetic improvement. During the twentieth century, oat landraces have increasingly been replaced by modern cultivars, resulting in loss of genetic diversity. However, landraces have considerable potential to improve disease and abiotic stress tolerance and may outperform cultivars under low input systems. In this work, we assembled a panel of 669 oat landraces from Mediterranean rim and 40 cultivated oat varieties and performed the first large-scale population genetic analysis of both red and white oat types of Mediterranean origin. We created a public database associated with an interactive map to visualize information for each accession. The oat collection was genotyped with 17,288 single-nucleotide polymorphism (SNP) loci to evaluate population structure and linkage disequilibrium (LD); to perform a genome-wide association study (GWAs) for heading date, a key character closely correlated with performance in this drought-prone area. Population genetic analysis using both structure and PCA distinguished two main groups composed of the red and white oats, respectively. The white oat group was further divided into two subgroups. LD decay was slower within white lines in linkage groups Mrg01, 02, 04, 12, 13, 15, 23, 33, whereas it was slower within red lines in Mrg03, 05, 06, 11, 21, 24, and 28. Association analysis showed several significant markers associated with heading date on linkage group Mrg13 in white oats and on Mrg01 and Mrg08 in red oats.

Population genomics of Mediterranean oat (A. sativa) reveals high genetic diversity and three loci for heading date

Genomic analysis of Mediterranean oats reveals high genetic diversity and three loci for adaptation to this environment. This information together with phenotyping and passport data, gathered in an interactive map, will be a vital resource for oat genetic improvement. During the twentieth century, oat landraces have increasingly been replaced by modern cultivars, resulting in loss of genetic diversity. However, landraces have considerable potential to improve disease and abiotic stress tolerance and may outperform cultivars under low input systems. In this work, we assembled a panel of 669 oat landraces from Mediterranean rim and 40 cultivated oat varieties and performed the first large-scale population genetic analysis of both red and white oat types of Mediterranean origin. We created a public database associated with an interactive map to visualize information for each accession. The oat collection was genotyped with 17,288 single-nucleotide polymorphism (SNP) loci to evaluate population structure and linkage disequilibrium (LD); to perform a genome-wide association study (GWAs) for heading date, a key character closely correlated with performance in this drought-prone area. Population genetic analysis using both structure and PCA distinguished two main groups composed of the red and white oats, respectively. The white oat group was further divided into two subgroups. LD decay was slower within white lines in linkage groups Mrg01, 02, 04, 12, 13, 15, 23, 33, whereas it was slower within red lines in Mrg03, 05, 06, 11, 21, 24, and 28. Association analysis showed several significant markers associated with heading date on linkage group Mrg13 in white oats and on Mrg01 and Mrg08 in red oats.

Comprehensive genotyping of a Brazilian cassava (Manihot esculenta Crantz) germplasm bank: insights into diversification and domestication

Brazilian cassava diversity was characterized through population genetics and clustering approaches, highlighting contrasted genetic groups and spatial genetic differentiation. Cassava (Manihot esculenta Crantz) is a major staple root crop of the tropics, originating from the Amazonian region. In this study, 3354 cassava landraces and modern breeding lines from the Embrapa Cassava Germplasm Bank (CGB) were characterized. All individuals were subjected to genotyping-by-sequencing (GBS), identifying 27,045 single-nucleotide polymorphisms (SNPs). Identity-by-state and population structure analyses revealed a unique set of 1536 individuals and 10 distinct genetic groups with heterogeneous linkage disequilibrium (LD). On this basis, a density of 1300-4700 SNP markers were selected for large-effect quantitative trait loci (QTL) detection. Identified genetic groups were further characterized for population genetics parameters including minor allele frequency (MAF), observed heterozygosity [Formula: see text], effective population size estimate [Formula: see text]) and polymorphism information content (PIC). Selection footprints and introgressions of M. glaziovii were detected. Spatial population structure analysis revealed five ancestral populations related to distinct Brazilian ecoregions. Estimation of historical relationships among identified populations suggests an early population split from Amazonian to Atlantic forest and Caatinga ecoregions and active gene flows. This study provides a thorough genetic characterization of ex situ germplasm resources from cassava's center of origin, South America, with results shedding light on Brazilian cassava characteristics and its biogeographical landscape. These findings support and facilitate the use of genetic resources in modern breeding programs including implementation of association mapping and genomic selection strategies.

Exploiting genetic diversity in two European maize landraces for improving Gibberella ear rot resistance using genomic tools

KEY MESSAGE

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

Deciphering the Genetic Diversity of Landraces With High-Throughput SNP Genotyping of DNA Bulks: Methodology and Application to the Maize 50k Array

Genebanks harbor original landraces carrying many original favorable alleles for mitigating biotic and abiotic stresses. Their genetic diversity remains, however, poorly characterized due to their large within genetic diversity. We developed a high-throughput, cheap and labor saving DNA bulk approach based on single-nucleotide polymorphism (SNP) Illumina Infinium HD array to genotype landraces. Samples were gathered for each landrace by mixing equal weights from young leaves, from which DNA was extracted. We then estimated allelic frequencies in each DNA bulk based on fluorescent intensity ratio (FIR) between two alleles at each SNP using a two step-approach. We first tested either whether the DNA bulk was monomorphic or polymorphic according to the two FIR distributions of individuals homozygous for allele A or B, respectively. If the DNA bulk was polymorphic, we estimated its allelic frequency by using a predictive equation calibrated on FIR from DNA bulks with known allelic frequencies. Our approach: (i) gives accurate allelic frequency estimations that are highly reproducible across laboratories, (ii) protects against false detection of allele fixation within landraces. We estimated allelic frequencies of 23,412 SNPs in 156 landraces representing American and European maize diversity. Modified Roger's genetic Distance between 156 landraces estimated from 23,412 SNPs and 17 simple sequence repeats using the same DNA bulks were highly correlated, suggesting that the ascertainment bias is low. Our approach is affordable, easy to implement and does not require specific bioinformatics support and laboratory equipment, and therefore should be highly relevant for large-scale characterization of genebanks for a wide range of species.

Genetic structure of a germplasm for hybrid breeding in rye (Secale cereale L.)

Rye (Secale cereale L.) responds strongly to changes in heterozygosity with hybrids portraying strong heterosis effect on all developmental and yielding characteristics. In order to achieve the highest potential heterosis effect parental lines must originate from genetically distinct gene pools. Here we report the first comprehensive SNP-based population study of an elite germplasm using fertilization control system for hybrid breeding in rye that is genetically different to the predominating P-type. In total 376 inbred lines from Nordic Seed Germany GmbH were genotyped for 4419 polymorphic SNPs. The aim of this study was to confirm and quantify the genetic separation of parental populations, unveil their genetic characteristics and investigate underlying population structures. Through a palette of complimenting analysis, we confirmed a strong genetic differentiation (FST = 0.332) of parental populations validating the germplasms suitability for hybrid breeding. These were, furthermore, found to diverge considerably in several features with the maternal population portraying a strong population structure characterized by a narrow genetic profile, small effective population size and high genome-wise linkage disequilibrium. We propose that the employed male-sterility system putatively constitutes a population determining parameter by influencing the rate of introducing novel genetic variation to the parental populations. Functional analysis of linkage blocks led to identification of a conserved segment on the distal 4RL chromosomal region annotated to the Rfp3 male-fertility restoration 'Pampa' type gene. Findings of our study emphasized the immediate value of comprehensive population studies on elite breeding germplasms as a pre-requisite for application of genomic-based breeding techniques, introgression of novel material and to support breeder decision-making.

Optimized breeding strategies to harness genetic resources with different performance levels

Background

The narrow genetic base of elite germplasm compromises long-term genetic gain and increases the vulnerability to biotic and abiotic stresses in unpredictable environmental conditions. Therefore, an efficient strategy is required to broaden the genetic base of commercial breeding programs while not compromising short-term variety release. Optimal cross selection aims at identifying the optimal set of crosses that balances the expected genetic value and diversity. We propose to consider genomic selection and optimal cross selection to recurrently improve genetic resources (i.e. pre-breeding), to bridge the improved genetic resources with elites (i.e. bridging), and to manage introductions into the elite breeding population. Optimal cross selection is particularly adapted to jointly identify bridging, introduction and elite crosses to ensure an overall consistency of the genetic base broadening strategy.

Results

We compared simulated breeding programs introducing donors with different performance levels, directly or indirectly after bridging. We also evaluated the effect of the training set composition on the success of introductions. We observed that with recurrent introductions of improved donors, it is possible to maintain the genetic diversity and increase mid- and long-term performances with only limited penalty at short-term. Considering a bridging step yielded significantly higher mid- and long-term genetic gain when introducing low performing donors. The results also suggested to consider marker effects estimated with a broad training population including donor by elite and elite by elite progeny to identify bridging, introduction and elite crosses.

Conclusion

Results of this study provide guidelines on how to harness polygenic variation present in genetic resources to broaden elite germplasm.

Disentangling group specific QTL allele effects from genetic background epistasis using admixed individuals in GWAS: An application to maize flowering

When handling a structured population in association mapping, group-specific allele effects may be observed at quantitative trait loci (QTLs) for several reasons: (i) a different linkage disequilibrium (LD) between SNPs and QTLs across groups, (ii) group-specific genetic mutations in QTL regions, and/or (iii) epistatic interactions between QTLs and other loci that have differentiated allele frequencies between groups. We present here a new genome-wide association (GWAS) approach to identify QTLs exhibiting such group-specific allele effects. We developed genetic materials including admixed progeny from different genetic groups with known genome-wide ancestries (local admixture). A dedicated statistical methodology was developed to analyze pure and admixed individuals jointly, allowing one to disentangle the factors causing the heterogeneity of allele effects across groups. This approach was applied to maize by developing an inbred "Flint-Dent" panel including admixed individuals that was evaluated for flowering time. Several associations were detected revealing a wide range of configurations of allele effects, both at known flowering QTLs (Vgt1, Vgt2 and Vgt3) and new loci. We found several QTLs whose effect depended on the group ancestry of alleles while others interacted with the genetic background. Our GWAS approach provides useful information on the stability of QTL effects across genetic groups and can be applied to a wide range of species.

Improving Short- and Long-Term Genetic Gain by Accounting for Within-Family Variance in Optimal Cross-Selection

The implementation of genomic selection in recurrent breeding programs raises the concern that a higher inbreeding rate could compromise the long-term genetic gain. An optimized mating strategy that maximizes the performance in progeny and maintains diversity for long-term genetic gain is therefore essential. The optimal cross-selection approach aims at identifying the optimal set of crosses that maximizes the expected genetic value in the progeny under a constraint on genetic diversity in the progeny. Optimal cross-selection usually does not account for within-family selection, i.e., the fact that only a selected fraction of each family is used as parents of the next generation. In this study, we consider within-family variance accounting for linkage disequilibrium between quantitative trait loci to predict the expected mean performance and the expected genetic diversity in the selected progeny of a set of crosses. These predictions rely on the usefulness criterion parental contribution (UCPC) method. We compared UCPC-based optimal cross-selection and the optimal cross-selection approach in a long-term simulated recurrent genomic selection breeding program considering overlapping generations. UCPC-based optimal cross-selection proved to be more efficient to convert the genetic diversity into short- and long-term genetic gains than optimal cross-selection. We also showed that, using the UCPC-based optimal cross-selection, the long-term genetic gain can be increased with only a limited reduction of the short-term commercial genetic gain.

QTL mapping and genome-wide prediction of heat tolerance in multiple connected populations of temperate maize

Climate change will lead to increasing heat stress in the temperate regions of the world. The objectives of this study were the following: (I) to assess the phenotypic and genotypic diversity of traits related to heat tolerance of maize seedlings and dissect their genetic architecture by quantitative trait locus (QTL) mapping, (II) to compare the prediction ability of genome-wide prediction models using various numbers of KASP (Kompetitive Allele Specific PCR genotyping) single nucleotide polymorphisms (SNPs) and RAD (restriction site-associated DNA sequencing) SNPs, and (III) to examine the prediction ability of intra-, inter-, and mixed-pool calibrations. For the heat susceptibility index of five of the nine studied traits, we identified a total of six QTL, each explaining individually between 7 and 9% of the phenotypic variance. The prediction abilities observed for the genome-wide prediction models were high, especially for the within-population calibrations, and thus, the use of such approaches to select for heat tolerance at seedling stage is recommended. Furthermore, we have shown that for the traits examined in our study, populations created from inter-pool crosses are suitable training sets to predict populations derived from intra-pool crosses.

Selection on Expected Maximum Haploid Breeding Values Can Increase Genetic Gain in Recurrent Genomic Selection

Genomic selection (GS) offers the possibility to estimate the effects of genome-wide molecular markers, which can be used to calculate genomic estimated breeding values (GEBVs) for individuals without phenotypes. GEBVs can serve as a selection criterion in recurrent GS, maximizing single-cycle but not necessarily long-term genetic gain. As simple genome-wide sums, GEBVs do not take into account other genomic information, such as the map positions of loci and linkage phases of alleles. Therefore, we herein propose a novel selection criterion called expected maximum haploid breeding value (EMBV). EMBV predicts the expected performance of the best among a limited number of gametes that a candidate contributes to the next generation, if selected. We used simulations to examine the performance of EMBV in comparison with GEBV as well as the recently proposed criterion optimal haploid value (OHV) and weighted GS. We considered different population sizes, numbers of selected candidates, chromosome numbers and levels of dominant gene action. Criterion EMBV outperformed GEBV after about 5 selection cycles, achieved higher long-term genetic gain and maintained higher diversity in the population. The other selection criteria showed the potential to surpass both GEBV and EMBV in advanced cycles of the breeding program, but yielded substantially lower genetic gain in early to intermediate cycles, which makes them unattractive for practical breeding. Moreover, they were largely inferior in scenarios with dominant gene action. Overall, EMBV shows high potential to be a promising alternative selection criterion to GEBV for recurrent genomic selection.

General and specific combining abilities in a maize (Zea mays L.) test-cross hybrid panel: relative importance of population structure and genetic divergence between parents

General and specific combining abilities of maize hybrids between 288 inbred lines and three tester lines were highly related to population structure and genetic distance inferred from SNP data. Many studies have attempted to provide reliable and quick methods to identify promising parental lines and combinations in hybrid breeding programs. Since the 1950s, maize germplasm has been organized into heterotic groups to facilitate the exploitation of heterosis. Molecular markers have proven efficient tools to address the organization of genetic diversity and the relationship between lines or populations. The aim of the present work was to investigate to what extent marker-based evaluations of population structure and genetic distance may account for general (GCA) and specific (SCA) combining ability components in a population composed of 800 inter and intra-heterotic group hybrids obtained by crossing 288 inbred lines and three testers. Our results illustrate a strong effect of groups identified by population structure analysis on both GCA and SCA components. Including genetic distance between parental lines of hybrids in the model leads to a significant decrease of SCA variance component and an increase in GCA variance component for all the traits. The latter suggests that this approach can be efficient to better estimate the potential combining ability of inbred lines when crossed with unrelated lines, and limits the consequences of tester choice. Significant residual GCA and SCA variance components of models taking into account structure and/or genetic distance highlight the variation available for breeding programs within structure groups.

Evaluation of LD decay and various LD-decay estimators in simulated and SNP-array data of tetraploid potato

The number of SNPs required for QTL discovery is justified by the distance at which linkage disequilibrium has decayed. Simulations and real potato SNP data showed how to estimate and interpret LD decay. The magnitude of linkage disequilibrium (LD) and its decay with genetic distance determine the resolution of association mapping, and are useful for assessing the desired numbers of SNPs on arrays. To study LD and LD decay in tetraploid potato, we simulated autotetraploid genotypes and used it to explore the dependence on: (1) the number of haplotypes in the population (the amount of genetic variation) and (2) the percentage of haplotype specific SNPs (hs-SNPs). Several estimators for short-range LD were explored, such as the average r ², median r ², and other percentiles of r ² (80, 90, and 95 %). For LD decay, we looked at LD_½,90, the distance at which the short-range LD is halved when using the 90 % percentile of r ² at short range, as estimator for LD. Simulations showed that the performance of various estimators for LD decay strongly depended on the number of haplotypes, although the real value of LD decay was not influenced very much by this number. The estimator LD_½,90 was chosen to evaluate LD decay in 537 tetraploid varieties. LD_½,90 values were 1.5 Mb for varieties released before 1945 and 0.6 Mb in varieties released after 2005. LD_½,90 values within three different subpopulations ranged from 0.7 to 0.9 Mb. LD_½,90 was 2.5 Mb for introgressed regions, indicating large haplotype blocks. In pericentromeric heterochromatin, LD decay was negligible. This study demonstrates that several related factors influencing LD decay could be disentangled, that no universal approach can be suggested, and that the estimation of LD decay has to be performed with great care and knowledge of the sampled material.

Association Mapping in Turkish Olive Cultivars Revealed Significant Markers Related to Some Important Agronomic Traits

Olive (Olea europaea L.) is one of the most important fruit trees especially in the Mediterranean countries due to high consumption of table olive and olive oil. In olive breeding, the phenotypic traits associated to fruit are the key factors that determine productivity. Association mapping has been used in some tree species and a lot of crop plant species, and here, we perform an initial effort to detect marker-trait associations in olive tree. In the current study, a total of 96 olive genotypes, including both oil and table olive genotypes from Turkish Olive GenBank Resources, were used to examine marker-trait associations. For olive genotyping, SNP, AFLP, and SSR marker data were selected from previously published study and association analysis was performed between these markers and 5 yield-related traits. Three different approaches were used to check for false-positive results in association tests, and association results obtained from these models were compared. Using the model utilizing both population structure and relative kinship, eleven associations were significant with FDR ≤ 0.05. The largest number of significant associations was detected for fruit weight and stone weight. Our results suggested that association mapping could be an effective approach for identifying marker-trait associations in olive genotypes, without the development of mapping populations. This study shows for the first time the use of association mapping for identifying molecular markers linked to important traits in olive tree.

Linkage disequilibrium, SNP frequency change due to selection, and association mapping in popcorn chromosome regions containing QTLs for quality traits

The objectives of this study were to assess linkage disequilibrium (LD) and selection-induced changes in single nucleotide polymorphism (SNP) frequency, and to perform association mapping in popcorn chromosome regions containing quantitative trait loci (QTLs) for quality traits. Seven tropical and two temperate popcorn populations were genotyped for 96 SNPs chosen in chromosome regions containing QTLs for quality traits. The populations were phenotyped for expansion volume, 100-kernel weight, kernel sphericity, and kernel density. The LD statistics were the difference between the observed and expected haplotype frequencies (D), the proportion of D relative to the expected maximum value in the population, and the square of the correlation between the values of alleles at two loci. Association mapping was based on least squares and Bayesian approaches. In the tropical populations, D-values greater than 0.10 were observed for SNPs separated by 100-150 Mb, while most of the D-values in the temperate populations were less than 0.05. Selection for expansion volume indirectly led to increase in LD values, population differentiation, and significant changes in SNP frequency. Some associations were observed for expansion volume and the other quality traits. The candidate genes are involved with starch, storage protein, lipid, and cell wall polysaccharides synthesis.

Geographical distribution of genetic diversity in Secale landrace and wild accessions

BACKGROUND

Rye, Secale cereale L., has historically been a crop of major importance and is still a key cereal in many parts of Europe. Single populations of cultivated rye have been shown to capture a large proportion of the genetic diversity present in the species, but the distribution of genetic diversity in subspecies and across geographical areas is largely unknown. Here we explore the structure of genetic diversity in landrace rye and relate it to that of wild and feral relatives.

RESULTS

A total of 567 SNPs were analysed in 434 individuals from 76 accessions of wild, feral and cultivated rye. Genetic diversity was highest in cultivated rye, slightly lower in feral rye taxa and significantly lower in the wild S. strictum Presl. and S. africanum Stapf. Evaluation of effects from ascertainment bias suggests underestimation of diversity primarily in S. strictum and S. africanum. Levels of ascertainment bias, STRUCTURE and principal component analyses all supported the proposed classification of S. africanum and S. strictum as a separate species from S. cereale. S. afghanicum (Vav.) Roshev, S. ancestrale Zhuk., S. dighoricum (Vav.) Roshev, S. segetale (Zhuk.) Roshev and S. vavilovii Grossh. seemed, in contrast, to share the same gene pool as S. cereale and their genetic clustering was more dependent on geographical origin than taxonomic classification. S. vavilovii was found to be the most likely wild ancestor of cultivated rye. Among cultivated rye landraces from Europe, Asia and North Africa five geographically discrete genetic clusters were identified. These had only limited overlap with major agro-climatic zones. Slash-and-burn rye from the Finnmark area in Scandinavia formed a distinct cluster with little similarity to other landrace ryes. Regional studies of Northern and South-West Europe demonstrate different genetic distribution patterns as a result of varying cultivation intensity.

CONCLUSIONS

With the exception of S. strictum and S. africanum different rye taxa share the majority of the genetic variation. Due to the vast sharing of genetic diversity within the S. cereale clade, ascertainment bias seems to be a lesser problem in rye than in predominantly selfing species. By exploiting within accession diversity geographic structure can be shown on a much finer scale than previously reported.

Identification of Genetic Differentiation between Waxy and Common Maize by SNP Genotyping

Waxy maize (Zea mays L. var. ceratina) is an important vegetable and economic crop that is thought to have originated from cultivated flint maize and most recently underwent divergence from common maize. In this study, a total of 110 waxy and 110 common maize inbred lines were genotyped with 3072 SNPs to evaluate the genetic diversity, population structure, and linkage disequilibrium decay as well as identify putative loci that are under positive selection. The results revealed abundant genetic diversity in the studied panel and that genetic diversity was much higher in common than in waxy maize germplasms. Principal coordinate analysis and neighbor-joining cluster analysis consistently classified the 220 accessions into two major groups and a mixed group with mixed ancestry. Subpopulation structure in both waxy and common maize sets were associated with the germplasm origin and corresponding heterotic groups. The LD decay distance (1500–2000 kb) in waxy maize was lower than that in common maize. Fourteen candidate loci were identified as under positive selection between waxy and common maize at the 99% confidence level. The information from this study can assist waxy maize breeders by enhancing parental line selection and breeding program design.

Genome-wide association and genomic prediction of resistance to maize lethal necrosis disease in tropical maize germplasm

KEY MESSAGE

Genome-wide association analysis in tropical and subtropical maize germplasm revealed that MLND resistance is influenced by multiple genomic regions with small to medium effects. The maize lethal necrosis disease (MLND) caused by synergistic interaction of Maize chlorotic mottle virus and Sugarcane mosaic virus, and has emerged as a serious threat to maize production in eastern Africa since 2011. Our objective was to gain insights into the genetic architecture underlying the resistance to MLND by genome-wide association study (GWAS) and genomic selection. We used two association mapping (AM) panels comprising a total of 615 diverse tropical/subtropical maize inbred lines. All the lines were evaluated against MLND under artificial inoculation. Both the panels were genotyped using genotyping-by-sequencing. Phenotypic variation for MLND resistance was significant and heritability was moderately high in both the panels. Few promising lines with high resistance to MLND were identified to be used as potential donors. GWAS revealed 24 SNPs that were significantly associated (P < 3 × 10(-5)) with MLND resistance. These SNPs are located within or adjacent to 20 putative candidate genes that are associated with plant disease resistance. Ridge regression best linear unbiased prediction with five-fold cross-validation revealed higher prediction accuracy for IMAS-AM panel (0.56) over DTMA-AM (0.36) panel. The prediction accuracy for both within and across panels is promising; inclusion of MLND resistance associated SNPs into the prediction model further improved the accuracy. Overall, the study revealed that resistance to MLND is controlled by multiple loci with small to medium effects and the SNPs identified by GWAS can be used as potential candidates in MLND resistance breeding program.

Prospects and limits of marker imputation in quantitative genetic studies in European elite wheat (Triticum aestivum L.)

Background

The main goal of our study was to investigate the implementation, prospects, and limits of marker imputation for quantitative genetic studies contrasting map-independent and map-dependent algorithms. We used a diversity panel consisting of 372 European elite wheat (Triticum aestivum L.) varieties, which had been genotyped with SNP arrays, and performed intensive simulation studies.

Results

Our results clearly showed that imputation accuracy was substantially higher for map-dependent compared to map-independent methods. The accuracy of marker imputation depended strongly on the linkage disequilibrium between the markers in the reference panel and the markers to be imputed. For the decay of linkage disequilibrium present in European wheat, we concluded that around 45,000 markers are needed for low cost, low-density marker profiling. This will facilitate high imputation accuracy, also for rare alleles. Genomic selection and diversity studies profited only marginally from imputing missing values. In contrast, the power of association mapping increased substantially when missing values were imputed.

Conclusions

Imputing missing values is especially of interest for an economic implementation of association mapping in breeding populations.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1366-y) contains supplementary material, which is available to authorized users.

A powerful tool for genome analysis in maize: development and evaluation of the high density 600 k SNP genotyping array

Background

High density genotyping data are indispensable for genomic analyses of complex traits in animal and crop species. Maize is one of the most important crop plants worldwide, however a high density SNP genotyping array for analysis of its large and highly dynamic genome was not available so far.

Results

We developed a high density maize SNP array composed of 616,201 variants (SNPs and small indels). Initially, 57 M variants were discovered by sequencing 30 representative temperate maize lines and then stringently filtered for sequence quality scores and predicted conversion performance on the array resulting in the selection of 1.2 M polymorphic variants assayed on two screening arrays. To identify high-confidence variants, 285 DNA samples from a broad genetic diversity panel of worldwide maize lines including the samples used for sequencing, important founder lines for European maize breeding, hybrids, and proprietary samples with European, US, semi-tropical, and tropical origin were used for experimental validation. We selected 616 k variants according to their performance during validation, support of genotype calls through sequencing data, and physical distribution for further analysis and for the design of the commercially available Affymetrix® Axiom® Maize Genotyping Array. This array is composed of 609,442 SNPs and 6,759 indels. Among these are 116,224 variants in coding regions and 45,655 SNPs of the Illumina® MaizeSNP50 BeadChip for study comparison. In a subset of 45,974 variants, apart from the target SNP additional off-target variants are detected, which show only a minor bias towards intermediate allele frequencies. We performed principal coordinate and admixture analyses to determine the ability of the array to detect and resolve population structure and investigated the extent of LD within a worldwide validation panel.

Conclusions

The high density Affymetrix® Axiom® Maize Genotyping Array is optimized for European and American temperate maize and was developed based on a diverse sample panel by applying stringent quality filter criteria to ensure its suitability for a broad range of applications. With 600 k variants it is the largest currently publically available genotyping array in crop species.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-823) contains supplementary material, which is available to authorized users.

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.

Genome-wide linkage disequilibrium in nine-spined stickleback populations

Variation in the extent and magnitude of genome-wide linkage disequilibrium (LD) among populations residing in different habitats has seldom been studied in wild vertebrates. We used a total of 109 microsatellite markers to quantify the level and patterns of genome-wide LD in 13 Fennoscandian nine-spined stickleback (Pungitius pungitius) populations from four (viz. marine, lake, pond, and river) different habitat types. In general, high magnitude (D' > 0.5) of LD was found both in freshwater and marine populations, and the magnitude of LD was significantly greater in inland freshwater than in marine populations. Interestingly, three coastal freshwater populations located in close geographic proximity to the marine populations exhibited similar LD patterns and genetic diversity as their marine neighbors. The greater levels of LD in inland freshwater compared with marine and costal freshwater populations can be explained in terms of their contrasting demographic histories: founder events, long-term isolation, small effective sizes, and population bottlenecks are factors likely to have contributed to the high levels of LD in the inland freshwater populations. In general, these findings shed new light on the patterns and extent of variation in genome-wide LD, as well as the ecological and evolutionary factors driving them.

Development and evaluation of the first high-throughput SNP array for common carp (Cyprinus carpio)

Background

A large number of single nucleotide polymorphisms (SNPs) have been identified in common carp (Cyprinus carpio) but, as yet, no high-throughput genotyping platform is available for this species. C. carpio is an important aquaculture species that accounts for nearly 14% of freshwater aquaculture production worldwide. We have developed an array for C. carpio with 250,000 SNPs and evaluated its performance using samples from various strains of C. carpio.

Results

The SNPs used on the array were selected from two resources: the transcribed sequences from RNA-seq data of four strains of C. carpio, and the genome re-sequencing data of five strains of C. carpio. The 250,000 SNPs on the resulting array are distributed evenly across the reference C.carpio genome with an average spacing of 6.6 kb. To evaluate the SNP array, 1,072 C. carpio samples were collected and tested. Of the 250,000 SNPs on the array, 185,150 (74.06%) were found to be polymorphic sites. Genotyping accuracy was checked using genotyping data from a group of full-siblings and their parents, and over 99.8% of the qualified SNPs were found to be reliable. Analysis of the linkage disequilibrium on all samples and on three domestic C.carpio strains revealed that the latter had the longer haplotype blocks. We also evaluated our SNP array on 80 samples from eight species related to C. carpio, with from 53,526 to 71,984 polymorphic SNPs. An identity by state analysis divided all the samples into three clusters; most of the C. carpio strains formed the largest cluster.

Conclusions

The Carp SNP array described here is the first high-throughput genotyping platform for C. carpio. Our evaluation of this array indicates that it will be valuable for farmed carp and for genetic and population biology studies in C. carpio and related species.

Fine genetic characterization of elite maize germplasm using high-throughput SNP genotyping

To investigate the genetic structure of Chinese maize germplasm, the MaizeSNP50 BeadChip with 56,110 single nucleotide polymorphisms (SNPs) was used to genotype a collection of 367 inbred lines widely used in maize breeding of China. A total of 41,819 informative SNPs with minor allele number of more than 0.05 were used to estimate the genetic diversity, relatedness, and linkage disequilibrium (LD) decay. Totally 1,015 SNPs evenly distributed in the genome were selected randomly to evaluate the population structure of these accessions. Results showed that two main groups could be determined i.e., the introduced germplasm and the local germplasm. Further, five subgroups corresponding to different heterotic groups, that is, Reid Yellow Dent (Reid), Lancaster Sure Crop (Lancaster), P group (P), Tang Sipingtou (TSPT), and Tem-tropic I group (Tem-tropic I), were determined. The genetic diversity of within subgroups was highest in the Tem-Tropic I and lowest in the P. Most lines in this panel showed limited relatedness with each other. Comparisons of gene diversity showed that there existed some conservative genetic regions in specific subgroups across the ten chromosomes, i.e., seven in the Lancaster, seven in the Reid, six in the TSPT, five in the P, and two in the Tem-Tropical I. In addition, the results also revealed that there existed fifteen conservative regions transmitted from Huangzaosi, an important foundation parent, to its descendants. These are important for further studies since the outcomes may provide clues to understand why Huangzaosi could become a foundation parent in Chinese maize breeding. For the panel of 367 elite lines, average LD distance was 391 kb and varied among different chromosomes as well as in different genomic regions of one chromosome. This analysis uncovered a high natural genetic diversity in the elite maize inbred set, suggesting that the panel can be used in association study, esp. for temperate regions.

A genome-wide association study reveals genes associated with fusarium ear rot resistance in a maize core diversity panel

Fusarium ear rot is a common disease of maize that affects food and feed quality globally. Resistance to the disease is highly quantitative, and maize breeders have difficulty incorporating polygenic resistance alleles from unadapted donor sources into elite breeding populations without having a negative impact on agronomic performance. Identification of specific allele variants contributing to improved resistance may be useful to breeders by allowing selection of resistance alleles in coupling phase linkage with favorable agronomic characteristics. We report the results of a genome-wide association study to detect allele variants associated with increased resistance to Fusarium ear rot in a maize core diversity panel of 267 inbred lines evaluated in two sets of environments. We performed association tests with 47,445 single-nucleotide polymorphisms (SNPs) while controlling for background genomic relationships with a mixed model and identified three marker loci significantly associated with disease resistance in at least one subset of environments. Each associated SNP locus had relatively small additive effects on disease resistance (±1.1% on a 0-100% scale), but nevertheless were associated with 3 to 12% of the genotypic variation within or across environment subsets. Two of three identified SNPs colocalized with genes that have been implicated with programmed cell death. An analysis of associated allele frequencies within the major maize subpopulations revealed enrichment for resistance alleles in the tropical/subtropical and popcorn subpopulations compared with other temperate breeding pools.

Adaptation of maize to temperate climates: mid-density genome-wide association genetics and diversity patterns reveal key genomic regions, with a major contribution of the Vgt2 (ZCN8) locus

The migration of maize from tropical to temperate climates was accompanied by a dramatic evolution in flowering time. To gain insight into the genetic architecture of this adaptive trait, we conducted a 50K SNP-based genome-wide association and diversity investigation on a panel of tropical and temperate American and European representatives. Eighteen genomic regions were associated with flowering time. The number of early alleles cumulated along these regions was highly correlated with flowering time. Polymorphism in the vicinity of the ZCN8 gene, which is the closest maize homologue to Arabidopsis major flowering time (FT) gene, had the strongest effect. This polymorphism is in the vicinity of the causal factor of Vgt2 QTL. Diversity was lower, whereas differentiation and LD were higher for associated loci compared to the rest of the genome, which is consistent with selection acting on flowering time during maize migration. Selection tests also revealed supplementary loci that were highly differentiated among groups and not associated with flowering time in our panel, whereas they were in other linkage-based studies. This suggests that allele fixation led to a lack of statistical power when structure and relatedness were taken into account in a linear mixed model. Complementary designs and analysis methods are necessary to unravel the architecture of complex traits. Based on linkage disequilibrium (LD) estimates corrected for population structure, we concluded that the number of SNPs genotyped should be at least doubled to capture all QTLs contributing to the genetic architecture of polygenic traits in this panel. These results show that maize flowering time is controlled by numerous QTLs of small additive effect and that strong polygenic selection occurred under cool climatic conditions. They should contribute to more efficient genomic predictions of flowering time and facilitate the dissemination of diverse maize genetic resources under a wide range of environments.

Comprehensive genotyping of the USA national maize inbred seed bank

BACKGROUND

Genotyping by sequencing, a new low-cost, high-throughput sequencing technology was used to genotype 2,815 maize inbred accessions, preserved mostly at the National Plant Germplasm System in the USA. The collection includes inbred lines from breeding programs all over the world.

RESULTS

The method produced 681,257 single-nucleotide polymorphism (SNP) markers distributed across the entire genome, with the ability to detect rare alleles at high confidence levels. More than half of the SNPs in the collection are rare. Although most rare alleles have been incorporated into public temperate breeding programs, only a modest amount of the available diversity is present in the commercial germplasm. Analysis of genetic distances shows population stratification, including a small number of large clusters centered on key lines. Nevertheless, an average fixation index of 0.06 indicates moderate differentiation between the three major maize subpopulations. Linkage disequilibrium (LD) decays very rapidly, but the extent of LD is highly dependent on the particular group of germplasm and region of the genome. The utility of these data for performing genome-wide association studies was tested with two simply inherited traits and one complex trait. We identified trait associations at SNPs very close to known candidate genes for kernel color, sweet corn, and flowering time; however, results suggest that more SNPs are needed to better explore the genetic architecture of complex traits.

CONCLUSIONS

The genotypic information described here allows this publicly available panel to be exploited by researchers facing the challenges of sustainable agriculture through better knowledge of the nature of genetic diversity.

Population structure, genetic diversity and linkage disequilibrium in elite winter wheat assessed with SNP and SSR markers

Modern genomics approaches rely on the availability of high-throughput and high-density genotyping platforms. A major breakthrough in wheat genotyping was the development of an SNP array. In this study, we used a diverse panel of 172 elite European winter wheat lines to evaluate the utility of the SNP array for genomic analyses in wheat germplasm derived from breeding programs. We investigated population structure and genetic relatedness and found that the results obtained with SNP and SSR markers differ. This suggests that additional research is required to determine the optimum approach for the investigation of population structure and kinship. Our analysis of linkage disequilibrium (LD) showed that LD decays within approximately 5-10 cM. Moreover, we found that LD is variable along chromosomes. Our results suggest that the number of SNPs needs to be increased further to obtain a higher coverage of the chromosomes. Taken together, SNPs can be a valuable tool for genomics approaches and for a knowledge-based improvement of wheat.

A developmental transcriptional network for maize defines coexpression modules

Here, we present a genome-wide overview of transcriptional circuits in the agriculturally significant crop species maize (Zea mays). We examined transcript abundance data at 50 developmental stages, from embryogenesis to senescence, for 34,876 gene models and classified genes into 24 robust coexpression modules. Modules were strongly associated with tissue types and related biological processes. Sixteen of the 24 modules (67%) have preferential transcript abundance within specific tissues. One-third of modules had an absence of gene expression in specific tissues. Genes within a number of modules also correlated with the developmental age of tissues. Coexpression of genes is likely due to transcriptional control. For a number of modules, key genes involved in transcriptional control have expression profiles that mimic the expression profiles of module genes, although the expression of transcriptional control genes is not unusually representative of module gene expression. Known regulatory motifs are enriched in several modules. Finally, of the 13 network modules with more than 200 genes, three contain genes that are notably clustered (P < 0.05) within the genome. This work, based on a carefully selected set of major tissues representing diverse stages of maize development, demonstrates the remarkable power of transcript-level coexpression networks to identify underlying biological processes and their molecular components.

High-density SNP-based genetic map development and linkage disequilibrium assessment in Brassica napus L

Background

High density genetic maps built with SNP markers that are polymorphic in various genetic backgrounds are very useful for studying the genetics of agronomical traits as well as genome organization and evolution. Simultaneous dense SNP genotyping of segregating populations and variety collections was applied to oilseed rape (Brassica napus L.) to obtain a high density genetic map for this species and to study the linkage disequilibrium pattern.

Results

We developed an integrated genetic map for oilseed rape by high throughput SNP genotyping of four segregating doubled haploid populations. A very high level of collinearity was observed between the four individual maps and a large number of markers (>59%) was common to more than two maps. The precise integrated map comprises 5764 SNP and 1603 PCR markers. With a total genetic length of 2250 cM, the integrated map contains a density of 3.27 markers (2.56 SNP) per cM. Genotyping of these mapped SNP markers in oilseed rape collections allowed polymorphism level and linkage disequilibrium (LD) to be studied across the different collections (winter vs spring, different seed quality types) and along the linkage groups. Overall, polymorphism level was higher and LD decayed faster in spring than in “00” winter oilseed rape types but this was shown to vary greatly along the linkage groups.

Conclusions

Our study provides a valuable resource for further genetic studies using linkage or association mapping, for marker assisted breeding and for Brassica napus sequence assembly and genome organization analyses.

Genomewide predictions from maize single-cross data

Maize (Zea mays L.) breeders evaluate many single-cross hybrids each year in multiple environments. Our objective was to determine the usefulness of genomewide predictions, based on marker effects from maize single-cross data, for identifying the best untested single crosses and the best inbreds within a biparental cross. We considered 479 experimental maize single crosses between 59 Iowa Stiff Stalk Synthetic (BSSS) inbreds and 44 non-BSSS inbreds. The single crosses were evaluated in multilocation experiments from 2001 to 2009 and the BSSS and non-BSSS inbreds had genotypic data for 669 single nucleotide polymorphism (SNP) markers. Single-cross performance was predicted by a previous best linear unbiased prediction (BLUP) approach that utilized marker-based relatedness and information on relatives, and from genomewide marker effects calculated by ridge-regression BLUP (RR-BLUP). With BLUP, the mean prediction accuracy (r(MG)) of single-cross performance was 0.87 for grain yield, 0.90 for grain moisture, 0.69 for stalk lodging, and 0.84 for root lodging. The BLUP and RR-BLUP models did not lead to r(MG) values that differed significantly. We then used the RR-BLUP model, developed from single-cross data, to predict the performance of testcrosses within 14 biparental populations. The r(MG) values within each testcross population were generally low and were often negative. These results were obtained despite the above-average level of linkage disequilibrium, i.e., r(2) between adjacent markers of 0.35 in the BSSS inbreds and 0.26 in the non-BSSS inbreds. Overall, our results suggested that genomewide marker effects estimated from maize single crosses are not advantageous (cofmpared with BLUP) for predicting single-cross performance and have erratic usefulness for predicting testcross performance within a biparental cross.

A connected set of genes associated with programmed cell death implicated in controlling the hypersensitive response in maize

Rp1-D21 is a maize auto-active resistance gene conferring a spontaneous hypersensitive response (HR) of variable severity depending on genetic background. We report an association mapping strategy based on the Mutant Assisted Gene Identification and Characterization approach to identify naturally occurring allelic variants associated with phenotypic variation in HR. Each member of a collection of 231 diverse inbred lines of maize constituting a high-resolution association mapping panel were crossed to a parental stock heterozygous for Rp1-D21, and the segregating F(1) generation testcrosses were evaluated for phenotypes associated with lesion severity for 2 years at two locations. A genome-wide scan for associations with HR was conducted with 47,445 SNPs using a linear mixed model that controlled for spurious associations due to population structure. Since the ability to identify candidate genes and the resolution of association mapping are highly influenced by linkage disequilibrium (LD), we examined the extent of genome-wide LD. On average, marker pairs separated by >10 kbp had an r(2) value of <0.1. Genomic regions surrounding SNPs significantly associated with HR traits were locally saturated with additional SNP markers to establish local LD structure and precisely identify candidate genes. Six significantly associated SNPs at five loci were detected. At each locus, the associated SNP was located within or immediately adjacent to candidate causative genes predicted to play significant roles in the control of programmed cell death and especially in ubiquitin pathway-related processes.

Genomic prediction of hybrid performance in maize with models incorporating dominance and population specific marker effects

Identifying high performing hybrids is an essential part of every maize breeding program. Genomic prediction of maize hybrid performance allows to identify promising hybrids, when they themselves or other hybrids produced from their parents were not tested in field trials. Using simulations, we investigated the effects of marker density (10, 1, 0.3 marker per mega base pair, Mbp(-1)), convergent or divergent parental populations, number of parents tested in other combinations (2, 1, 0), genetic model (including population-specific and/or dominance marker effects or not), and estimation method (GBLUP or BayesB) on the prediction accuracy. We based our simulations on marker genotypes of Central European flint and dent inbred lines from an ongoing maize breeding program. To simulate convergent or divergent parent populations, we generated phenotypes by assigning QTL to markers with similar or very different allele frequencies in both pools, respectively. Prediction accuracies increased with marker density and number of parents tested and were higher under divergent compared with convergent parental populations. Modeling marker effects as population-specific slightly improved prediction accuracy under lower marker densities (1 and 0.3 Mbp(-1)). This indicated that modeling marker effects as population-specific will be most beneficial under low linkage disequilibrium. Incorporating dominance effects improved prediction accuracies considerably for convergent parent populations, where dominance results in major contributions of SCA effects to the genetic variance among inter-population hybrids. While the general trends regarding the effects of the aforementioned influence factors on prediction accuracy were similar for GBLUP and BayesB, the latter method produced significantly higher accuracies for models incorporating dominance.

Comparison of biometrical approaches for QTL detection in multiple segregating families

Detection of QTL in multiple segregating families possesses many advantages over the classical QTL mapping in biparental populations. It has thus become increasingly popular, and different biometrical approaches are available to analyze such data sets. We empirically compared an approach based on linkage mapping methodology with an association mapping approach. To this end, we used a large population of 788 elite maize lines derived from six biparental families genotyped with 857 SNP markers. In addition, we constructed genetic maps with reduced marker densities to assess the dependency of the performance of both mapping approaches on the marker density. We used cross-validation and resample model averaging and found that while association mapping performed better under high marker densities, this was reversed under low marker densities. In addition to main effect QTL, we also detected epistatic interactions. Our results suggest that both approaches will profit from a further increase in marker density and that a cross-validation should be applied irrespective of the biometrical approach.

Genomewide predictions from maize single-cross data

Maize (Zea mays L.) breeders evaluate many single-cross hybrids each year in multiple environments. Our objective was to determine the usefulness of genomewide predictions, based on marker effects from maize single-cross data, for identifying the best untested single crosses and the best inbreds within a biparental cross. We considered 479 experimental maize single crosses between 59 Iowa Stiff Stalk Synthetic (BSSS) inbreds and 44 non-BSSS inbreds. The single crosses were evaluated in multilocation experiments from 2001 to 2009 and the BSSS and non-BSSS inbreds had genotypic data for 669 single nucleotide polymorphism (SNP) markers. Single-cross performance was predicted by a previous best linear unbiased prediction (BLUP) approach that utilized marker-based relatedness and information on relatives, and from genomewide marker effects calculated by ridge-regression BLUP (RR-BLUP). With BLUP, the mean prediction accuracy (r(MG)) of single-cross performance was 0.87 for grain yield, 0.90 for grain moisture, 0.69 for stalk lodging, and 0.84 for root lodging. The BLUP and RR-BLUP models did not lead to r(MG) values that differed significantly. We then used the RR-BLUP model, developed from single-cross data, to predict the performance of testcrosses within 14 biparental populations. The r(MG) values within each testcross population were generally low and were often negative. These results were obtained despite the above-average level of linkage disequilibrium, i.e., r(2) between adjacent markers of 0.35 in the BSSS inbreds and 0.26 in the non-BSSS inbreds. Overall, our results suggested that genomewide marker effects estimated from maize single crosses are not advantageous (cofmpared with BLUP) for predicting single-cross performance and have erratic usefulness for predicting testcross performance within a biparental cross.

Diversity and linkage disequilibrium features in a composite public/private dent maize panel: consequences for association genetics as evaluated from a case study using flowering time

Recent progress in genotyping and resequencing techniques have opened new opportunities for deciphering quantitative trait variation by looking for associations between traits of interest and polymorphisms in panels of diverse inbred lines. Association mapping raises specific issues related to the choice of appropriate (i) panels and marker-densities and (ii) statistical methods to capture associations. In this study, we used a panel of 314 maize inbred lines from the dent pool, composed of inbred material from public institutes (113 inbred lines) and a private company (201 inbred lines). We showed that local LD was higher and genetic diversity lower in the material of private origin than in the public material. We compared the results obtained by different software for identifying population structure and computing relatedness among lines, and ran association tests for earliness related traits. Our results confirmed the importance of the mite polymorphism of Vgt1 on flowering time, but also showed that its effect can be captured by zmRap2.7 polymorphisms located 70 kb apart. We also highlighted associations with polymorphisms within genes putatively involved in lignin biosynthesis pathway, which deserve further investigations.

Mapping QTL for agronomic traits in breeding populations

Detection of quantitative trait loci (QTL) in breeding populations offers the advantage that these QTL are of direct relevance for the improvement of crops via knowledge-based breeding. As phenotypic data are routinely generated in breeding programs and the costs for genotyping are constantly decreasing, it is tempting to exploit this information to unravel the genetic architecture underlying important agronomic traits in crops. This review characterizes the germplasm from breeding populations available for QTL detection, provides a classification of the different QTL mapping approaches that are available, and highlights important considerations concerning study design and biometrical models suitable for QTL analysis.

Genomic prediction of hybrid performance in maize with models incorporating dominance and population specific marker effects

Identifying high performing hybrids is an essential part of every maize breeding program. Genomic prediction of maize hybrid performance allows to identify promising hybrids, when they themselves or other hybrids produced from their parents were not tested in field trials. Using simulations, we investigated the effects of marker density (10, 1, 0.3 marker per mega base pair, Mbp(-1)), convergent or divergent parental populations, number of parents tested in other combinations (2, 1, 0), genetic model (including population-specific and/or dominance marker effects or not), and estimation method (GBLUP or BayesB) on the prediction accuracy. We based our simulations on marker genotypes of Central European flint and dent inbred lines from an ongoing maize breeding program. To simulate convergent or divergent parent populations, we generated phenotypes by assigning QTL to markers with similar or very different allele frequencies in both pools, respectively. Prediction accuracies increased with marker density and number of parents tested and were higher under divergent compared with convergent parental populations. Modeling marker effects as population-specific slightly improved prediction accuracy under lower marker densities (1 and 0.3 Mbp(-1)). This indicated that modeling marker effects as population-specific will be most beneficial under low linkage disequilibrium. Incorporating dominance effects improved prediction accuracies considerably for convergent parent populations, where dominance results in major contributions of SCA effects to the genetic variance among inter-population hybrids. While the general trends regarding the effects of the aforementioned influence factors on prediction accuracy were similar for GBLUP and BayesB, the latter method produced significantly higher accuracies for models incorporating dominance.

Genome-wide evaluation of genetic diversity and linkage disequilibrium in winter and spring triticale (x Triticosecale Wittmack)

Background

Recent advances in genotyping with high-density markers nowadays enable genome-wide genomic analyses in crops. A detailed characterisation of the population structure and linkage disequilibrium (LD) is essential for the application of genomic approaches and consequently for knowledge-based breeding. In this study we used the triticale-specific DArT array to analyze population structure, genetic diversity, and LD in a worldwide set of 161 winter and spring triticale lines.

Results

The principal coordinate analysis revealed that the first principal coordinate divides the triticale population into two clusters according to their growth habit. The density distributions of the first ten principal coordinates revealed that several show a distribution indicative of population structure. In addition, we observed relatedness within growth habits which was higher among the spring types than among the winter types. The genome-wide analysis of polymorphic information content (PIC) showed that the PIC is variable among and along chromosomes and that especially the R genome of spring types possesses a reduced genetic diversity. We also found that several chromosomes showed regions of high genetic distance between the two growth habits, indicative of divergent selection. Regarding linkage disequilibrium, the A and B genomes showed a similar LD of 0.24 for closely linked markers and a decay within approximately 12 cM. LD in the R genome was lower with 0.19 and decayed within a shorter map distance of approximately 5 cM. The extent of LD was generally higher for the spring types compared to the winter types. In addition, we observed strong variability of LD along the chromosomes.

Conclusions

Our results confirm winter and spring growth habit are the major contributors to population structure in triticale, and a family structure exists in both growth types. The specific patterns of genetic diversity observed within these types, such as the low diversity on some rye chromosomes of spring habits, provide a basis for targeted broadening of the available breeding germplasm. In addition, the genome-wide analysis of the extent and the pattern of LD will assist scientists and breeders alike in the implementation and the interpretation of association mapping in triticale.

Genome-wide SNP identification in multiple morphotypes of allohexaploid tall fescue (Festuca arundinacea Schreb)

BACKGROUND

Single nucleotide polymorphisms (SNPs) provide essential tools for the advancement of research in plant genomics, and the development of SNP resources for many species has been accelerated by the capabilities of second-generation sequencing technologies. The current study aimed to develop and use a novel bioinformatic pipeline to generate a comprehensive collection of SNP markers within the agriculturally important pasture grass tall fescue; an outbreeding allopolyploid species displaying three distinct morphotypes: Continental, Mediterranean and rhizomatous.

RESULTS

A bioinformatic pipeline was developed that successfully identified SNPs within genotypes from distinct tall fescue morphotypes, following the sequencing of 414 polymerase chain reaction (PCR) - generated amplicons using 454 GS FLX technology. Equivalent amplicon sets were derived from representative genotypes of each morphotype, including six Continental, five Mediterranean and one rhizomatous. A total of 8,584 and 2,292 SNPs were identified with high confidence within the Continental and Mediterranean morphotypes respectively. The success of the bioinformatic approach was demonstrated through validation (at a rate of 70%) of a subset of 141 SNPs using both SNaPshot™ and GoldenGate™ assay chemistries. Furthermore, the quantitative genotyping capability of the GoldenGate™ assay revealed that approximately 30% of the putative SNPs were accessible to co-dominant scoring, despite the hexaploid genome structure. The sub-genome-specific origin of each SNP validated from Continental tall fescue was predicted using a phylogenetic approach based on comparison with orthologous sequences from predicted progenitor species.

CONCLUSIONS

Using the appropriate bioinformatic approach, amplicon resequencing based on 454 GS FLX technology is an effective method for the identification of polymorphic SNPs within the genomes of Continental and Mediterranean tall fescue. The GoldenGate™ assay is capable of high-throughput co-dominant SNP allele detection, and minimises the problems associated with SNP genotyping in a polyploid by effectively reducing the complexity to a diploid system. This SNP collection may now be refined and used in applications such as cultivar identification, genetic linkage map construction, genome-wide association studies and genomic selection in tall fescue. The bioinformatic pipeline described here represents an effective general method for SNP discovery within outbreeding allopolyploid species.

Mapping QTL for agronomic traits in breeding populations

Detection of quantitative trait loci (QTL) in breeding populations offers the advantage that these QTL are of direct relevance for the improvement of crops via knowledge-based breeding. As phenotypic data are routinely generated in breeding programs and the costs for genotyping are constantly decreasing, it is tempting to exploit this information to unravel the genetic architecture underlying important agronomic traits in crops. This review characterizes the germplasm from breeding populations available for QTL detection, provides a classification of the different QTL mapping approaches that are available, and highlights important considerations concerning study design and biometrical models suitable for QTL analysis.

Genome-wide association mapping of flowering time and northern corn leaf blight (Setosphaeria turcica) resistance in a vast commercial maize germplasm set

BACKGROUND

Setosphaeria turcica is a fungal pathogen that causes northern corn leaf blight (NCLB) which is a serious foliar disease in maize. In order to unravel the genetic architecture of the resistance against this disease, a vast association mapping panel comprising 1487 European maize inbred lines was used to (i) identify chromosomal regions affecting flowering time (FT) and northern corn leaf blight (NCLB) resistance, (ii) examine the epistatic interactions of the identified chromosomal regions with the genetic background on an individual molecular marker basis, and (iii) dissect the correlation between NCLB resistance and FT.

RESULTS

The single marker analyses performed for 8 244 single nucleotide polymorphism (SNP) markers revealed seven, four, and four SNP markers significantly (α=0.05, amplicon wise Bonferroni correction) associated with FT, NCLB, and NCLB resistance corrected for FT, respectively. These markers explained individually between 0.36 and 14.29% of the genetic variance of the corresponding trait.

CONCLUSIONS

The very well interpretable pattern of SNP associations observed for FT suggested that data from applied plant breeding programs can be used to dissect polygenic traits. This in turn indicates that the associations identified for NCLB resistance might be successfully used in marker-assisted selection programs. Furthermore, the associated genes are also of interest for further research concerning the mechanism of resistance to NCLB and plant diseases in general, because some of the associated genes have not been mentioned in this context so far.

Accuracy of genomic selection in European maize elite breeding populations

Genomic selection is a promising breeding strategy for rapid improvement of complex traits. The objective of our study was to investigate the prediction accuracy of genomic breeding values through cross validation. The study was based on experimental data of six segregating populations from a half-diallel mating design with 788 testcross progenies from an elite maize breeding program. The plants were intensively phenotyped in multi-location field trials and fingerprinted with 960 SNP markers. We used random regression best linear unbiased prediction in combination with fivefold cross validation. The prediction accuracy across populations was higher for grain moisture (0.90) than for grain yield (0.58). The accuracy of genomic selection realized for grain yield corresponds to the precision of phenotyping at unreplicated field trials in 3-4 locations. As for maize up to three generations are feasible per year, selection gain per unit time is high and, consequently, genomic selection holds great promise for maize breeding programs.

Genomic and metabolic prediction of complex heterotic traits in hybrid maize

Maize is both an exciting model organism in plant genetics and also the most important crop worldwide for food, animal feed and bioenergy production. Recent genome-wide association and metabolic profiling studies aimed to resolve quantitative traits to their causal genetic loci and key metabolic regulators. Here we present a complementary approach that exploits large-scale genomic and metabolic information to predict complex, highly polygenic traits in hybrid testcrosses. We crossed 285 diverse Dent inbred lines from worldwide sources with two testers and predicted their combining abilities for seven biomass- and bioenergy-related traits using 56,110 SNPs and 130 metabolites. Whole-genome and metabolic prediction models were built by fitting effects for all SNPs or metabolites. Prediction accuracies ranged from 0.72 to 0.81 for SNPs and from 0.60 to 0.80 for metabolites, allowing a reliable screening of large collections of diverse inbred lines for their potential to create superior hybrids.