Matthias Frisch

Linkage disequilibrium in European elite maize germplasm investigated with SSRs

Information about the extent and genomic distribution of linkage disequilibrium (LD) is of fundamental importance for association mapping. The main objectives of this study were to (1) investigate genetic diversity within germplasm groups of elite European maize (Zea mays L.) inbred lines, (2) examine the population structure of elite European maize germplasm, and (3) determine the extent and genomic distribution of LD between pairs of simple sequence repeat (SSR) markers. We examined genetic diversity and LD in a cross section of European and US elite breeding material comprising 147 inbred lines genotyped with 100 SSR markers. For gene diversity within each group, significant (P<0.05) differences existed among the groups. The LD was significant (P<0.05) for 49% of the SSR marker pairs in the 80 flint lines and for 56% of the SSR marker pairs in the 57 dent lines. The ratio of linked to unlinked loci in LD was 1.1 for both germplasm groups. The high incidence of LD suggests that the extent of LD between SSR markers should allow the detection of marker-phenotype associations in a genome scan. However, our results also indicate that a high proportion of the observed LD is generated by forces, such as relatedness, population stratification, and genetic drift, which cause a high risk of detecting false positives in association mapping.

Use of SSRs for establishing heterotic groups in subtropical maize

Abstract Heterotic groups and patterns are of fundamental importance in hybrid breeding. The objectives of our research were to: (1) investigate the relationship of simple sequence repeats (SSR) based genetic distances between populations and panmictic midparent heterosis (PMPH) in a broad range of CIMMYT maize germplasm, (2) evaluate the usefulness of SSR markers for defining heterotic groups and patterns in subtropical germplasm, and (3) examine applications of SSR markers for broadening heterotic groups by systematic introgression of other germplasm. Published data of two diallels and one factorial evaluated for grain yield were re-analyzed to calculate the PMPH in population hybrids. Additionally, 20 pools and populations widely used in CIMMYTs breeding program were assayed with 83 SSR markers covering the entire maize genome. Correlations of squared modified Rogers distance (MRD2) and PMPH were mostly positive and significant, but adaption problems caused deviations in some cases. For intermediate- and early-maturity subtropical germplasm, two heterotic groups could be suggested consisting of a flint and dent composite. We concluded that the relationships between the populations obtained by SSR analyses are in excellent agreement with pedigree information. SSR markers are a valuable complementation to field trials for identifying heterotic groups and can be used to introgress exotic germplasm systematically.

Grouping of accessions of Mexican races of maize revisited with SSR markers

Mexican races of maize (Zea mays L.) represent a valuable genetic resource for breeding and genetic surveys. We applied simple sequence repeat (SSR) markers to characterize 25 accessions of races of maize from Mexico. Our objectives were to (1) study the molecular genetic diversity within and among these accessions and (2) examine their relationships as assumed previously on the basis of morphological data. A total of 497 individuals were fingerprinted with 25 SSR markers. We observed a high total number of alleles (7.84 alleles per locus) and total gene diversity (0.61), confirming the broad genetic base of the maize races from Mexico. In addition, the accessions were grouped into distinct racial complexes on the basis of a model-based clustering approach. The principal coordinate analyses of the four Modern Incipient hybrids corroborated the proposed parental races of Chalqueño, Cónico Norteño, Celaya, and Bolita on the basis of the morphological data. Consequently, for some of the accessions, hybridizations provide a clue that can further be used to explain the associations among the Mexican races of maize.

Population genetic simulation and data analysis with Plabsoft

Computer simulations are a useful tool to solve problems in population genetics for which no analytical solutions are available. We developed Plabsoft, a powerful and flexible software for population genetic simulation and data analysis. Various mating systems can be simulated, comprising planned crosses, random mating, partial selfing, selfing, single-seed descent, double haploids, topcrosses, and factorials. Selection can be simulated according to selection indices based on phenotypic values and/or molecular marker scores. Data analysis routines are provided to analyze simulated and experimental datasets for allele and genotype frequencies, genotypic and phenotypic values and variances, molecular genetic diversity, linkage disequilibrium, and parameters to optimize marker-assisted backcrossing programs. Plabsoft has already been employed in numerous studies, we chose some of them to illustrate the functionality of the software.

Comparison of Linkage Disequilibrium in Elite European Maize Inbred Lines using AFLP and SSR Markers

Application of association mapping to plant breeding populations has the potential to revolutionize plant genetics. The main objectives of this study were to (i) investigate the extent and genomic distribution of linkage disequilibrium (LD) between pairs of amplified fragment length polymorphism (AFLP) markers, (ii) compare these results with those obtained with simple sequence repeat (SSR) markers, and (iii) compare the usefulness of AFLP and SSR markers for genomewide association mapping in plant breeding populations. We examined LD in a cross-section of 72 European elite inbred lines genotyped with 452 AFLP and 93 SSR markers. LD was significant (p < 0.05) for about 15% of the AFLP marker pairs and for about 49% of the SSR marker pairs in each of the two germplasm groups, flint and dent. In both germplasm groups the ratio of linked to unlinked loci pairs in LD was higher for AFLPs than for SSRs. The observation of LD due to linkage for both marker types suggested that genome-wide association mapping should be possible using either AFLPs or SSRs. The results of our study indicated that SSRs should be favored over AFLPs but the opposite applies to populations with a long history of recombination.

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

In hybrid breeding, the prediction of hybrid performance (HP) is extremely important as it is difficult to evaluate inbred lines in numerous cross combinations. Recent developments such as doubled haploid production and molecular marker technologies have enhanced the prospects of marker-based HP prediction to accelerate the breeding process. Our objectives were to (1) predict HP using a combined analysis of hybrids and parental lines from a breeding program, (2) evaluate the use of molecular markers in addition to phenotypic and pedigree data, (3) evaluate the combination of line per se data with marker-based estimates, (4) study the effect of the number of tested parents, and (5) assess the advantage of haplotype blocks. An unbalanced dataset of 400 hybrids from 9 factorial crosses tested in different experiments and data of 79 inbred parents were subjected to combined analyses with a mixed linear model. Marker data of the inbreds were obtained with 20 AFLP primer–enzyme combinations. Cross-validation was used to assess the performance prediction of hybrids of which no or only one parental line was testcross evaluated. For HP prediction, the highest proportion of explained variance (R2), 46% for grain yield (GY) and 70% for grain dry matter content (GDMC), was obtained from line per se best linear unbiased prediction (BLUP) estimates plus marker effects associated with mid-parent heterosis (TEAM-LM). Our study demonstrated that HP was efficiently predicted using molecular markers even for GY when testcross data of both parents are not available. This can help in improving greatly the efficiency of commercial hybrid breeding programs.

Genome-wide association mapping unravels the genetic control of seed germination and vigor in Brassica napus

Rapid and uniform seed germination is a crucial prerequisite for crop establishment and high yield levels in crop production. A disclosure of genetic factors contributing to adequate seed vigor would help to further increase yield potential and stability. Here we carried out a genome-wide association study in order to define genomic regions influencing seed germination and early seedling growth in oilseed rape (Brassica napus L.). A population of 248 genetically diverse winter-type B. napus accessions was genotyped with the Brassica 60k SNP Illumina genotyping array. Automated high-throughput in vitro phenotyping provided extensive data for multiple traits related to germination and early vigor, such as germination speed, absolute germination rate and radicle elongation. The data obtained indicate that seed germination and radicle growth are strongly environmentally dependent, but could nevertheless be substantially improved by genomic-based breeding. Conditions during seed production and storage were shown to have a profound effect on seed vigor, and a variable manifestation of seed dormancy appears to contribute to differences in germination performance in B. napus. Several promising positional and functional candidate genes could be identified within the genomic regions associated with germination speed, absolute germination rate, radicle growth and thousand seed weight. These include B. napus orthologs of the Arabidopsis thaliana genes SNOWY COTYLEDON 1 (SCO1), ARABIDOPSIS TWO-COMPONENT RESPONSE REGULATOR (ARR4), and ARGINYL-t-RNA PROTEIN TRANSFERASE 1 (ATE1), which have been shown previously to play a role in seed germination and seedling growth in A. thaliana.

Genome-based prediction of test cross performance in two subsequent breeding cycles

Genome-based prediction of genetic values is expected to overcome shortcomings that limit the application of QTL mapping and marker-assisted selection in plant breeding. Our goal was to study the genome-based prediction of test cross performance with genetic effects that were estimated using genotypes from the preceding breeding cycle. In particular, our objectives were to employ a ridge regression approach that approximates best linear unbiased prediction of genetic effects, compare cross validation with validation using genetic material of the subsequent breeding cycle, and investigate the prospects of genome-based prediction in sugar beet breeding. We focused on the traits sugar content and standard molasses loss (ML) and used a set of 310 sugar beet lines to estimate genetic effects at 384 SNP markers. In cross validation, correlations >0.8 between observed and predicted test cross performance were observed for both traits. However, in validation with 56 lines from the next breeding cycle, a correlation of 0.8 could only be observed for sugar content, for standard ML the correlation reduced to 0.4. We found that ridge regression based on preliminary estimates of the heritability provided a very good approximation of best linear unbiased prediction and was not accompanied with a loss in prediction accuracy. We conclude that prediction accuracy assessed with cross validation within one cycle of a breeding program can not be used as an indicator for the accuracy of predicting lines of the next cycle. Prediction of lines of the next cycle seems promising for traits with high heritabilities.

Dissecting grain yield pathways and their interactions with grain dry matter content by a two-step correlation approach with maize seedling transcriptome

BackgroundThe importance of maize for human and animal nutrition, but also as a source for bio-energy is rapidly increasing. Maize yield is a quantitative trait controlled by many genes with small effects, spread throughout the genome. The precise location of the genes and the identity of the gene networks underlying maize grain yield is unknown. The objective of our study was to contribute to the knowledge of these genes and gene networks by transcription profiling with microarrays.ResultsWe assessed the grain yield and grain dry matter content (an indicator for early maturity) of 98 maize hybrids in multi-environment field trials. The gene expression in seedlings of the parental inbred lines, which have four different genetic backgrounds, was assessed with genome-scale oligonucleotide arrays. We identified genes associated with grain yield and grain dry matter content using a newly developed two-step correlation approach and found overlapping gene networks for both traits. The underlying metabolic pathways and biological processes were elucidated. Genes involved in sucrose degradation and glycolysis, as well as genes involved in cell expansion and endocycle were found to be associated with grain yield.ConclusionsOur results indicate that the capability of providing energy and substrates, as well as expanding the cell at the seedling stage, highly influences the grain yield of hybrids. Knowledge of these genes underlying grain yield in maize can contribute to the development of new high yielding varieties.

Identification of essentially derived varieties with molecular markers: an approach based on statistical test theory and computer simulations.

Genetic similarities (GS) based on molecular markers have been proposed as a tool for identification of essentially derived varieties (EDVs). Nevertheless, scientifically reliable criteria for discrimination of EDVs and independently derived varieties with GS estimates are scanty, and implementation into practical breeding has not yet taken place. Our objectives were to (1) assess the influence of chromosome number and length, marker density, and distribution, as well as the degree of polymorphism between the parental inbreds on the distribution of GS between parental inbreds and their progenies [GS(P1,O)] derived from F2 and different backcross populations and (2) evaluate these factors with regard to the power for distinguishing F2- versus BC1- and BC1- versus BC2-derived lines with molecular markers. We developed an approach based on statistical test theory for the identification of EDVs with molecular markers. Standard deviations and overlaps of distributions of GS(P1,O) of F2-, BC1-, and BC2-derived lines were smaller with (1) increasing chromosome number and length, (2) increasing marker density, and (3) uniformly instead of randomly distributed markers, approaching a lower boundary determined by the genetic parameters. The degree of polymorphism between the parental inbreds influenced the power only if the remaining number of polymorphic markers was low. Furthermore, suggestions are made for (1) determining the number of markers required to ascertain a given power and (2) EDV identification procedures.