A comprehensive study of the genomic differentiation between temperate Dent and Flint maize.

BACKGROUND: Dent and Flint represent two major germplasm pools exploited in maize breeding. Several traits differentiate the two pools, like cold tolerance, early vigor, and flowering time. A comparative investigation of their genomic architecture relevant for quantitative trait expression has not been reported so far. Understanding the genomic differences between germplasm pools may contribute to a better understanding of the complementarity in heterotic patterns exploited in hybrid breeding and of mechanisms involved in adaptation to different environments. RESULTS: We perform whole-genome screens for signatures of selection specific to temperate Dent and Flint maize by comparing high-density genotyping data of 70 American and European Dent and 66 European Flint inbred lines. We find 2.2 % and 1.4 % of the genes are under selective pressure, respectively, and identify candidate genes associated with agronomic traits known to differ between the two pools. Taking flowering time as an example for the differentiation between Dent and Flint, we investigate candidate genes involved in the flowering network by phenotypic analyses in a Dent-Flint introgression library and find that the Flint haplotypes of the candidates promote earlier flowering. Within the flowering network, the majority of Flint candidates are associated with endogenous pathways in contrast to Dent candidate genes, which are mainly involved in response to environmental factors like light and photoperiod. The diversity patterns of the candidates in a unique panel of more than 900 individuals from 38 European landraces indicate a major contribution of landraces from France, Germany, and Spain to the candidate gene diversity of the Flint elite lines. CONCLUSIONS: In this study, we report the investigation of pool-specific differences between temperate Dent and Flint on a genome-wide scale. The identified candidate genes represent a promising source for the functional investigation of pool-specific haplotypes in different genetic backgrounds and for the evaluation of their potential for future crop improvement like the adaptation to specific environments.

Improving resistance to the European corn borer: a comprehensive study in elite maize using QTL mapping and genome-wide prediction.

KEY MESSAGE: The efficiency of marker-assisted selection for native resistance to European corn borer stalk damage can be increased when progressing from a QTL-based towards a genome-wide approach. Marker-assisted selection (MAS) has been shown to be effective in improving resistance to the European corn borer (ECB) in maize. In this study, we investigated the performance of whole-genome-based selection, relative to selection based on individual quantitative trait loci (QTL), for resistance to ECB stalk damage in European elite maize. Three connected biparental populations, comprising 590 doubled haploid (DH) lines, were genotyped with high-density single nucleotide polymorphism markers and phenotyped under artificial and natural infestation in 2011. A subset of 195 DH lines was evaluated in the following year as lines per se and as testcrosses. Resistance was evaluated based on stalk damage ratings, the number of feeding tunnels in the stalk and tunnel length. We performed individual- and joint-population QTL analyses and compared the cross-validated predictive abilities of the QTL models with genomic best linear unbiased prediction (GBLUP). For all traits, the GBLUP model consistently outperformed the QTL model despite the detection of QTL with sizeable effects. For stalk damage rating, GBLUP's predictive ability exceeded at times 0.70. Model training based on DH line per se performance was efficient in predicting stalk breakage in testcrosses. We conclude that the efficiency of MAS for ECB stalk damage resistance can be increased considerably when progressing from a QTL-based towards a genome-wide approach. With the availability of native ECB resistance in elite European maize germplasm, our results open up avenues for the implementation of an integrated genome-based selection approach for the simultaneous improvement of yield, maturity and ECB resistance.

Stable carbon isotope discrimination is under genetic control in the C4 species maize with several genomic regions influencing trait expression.

In plants with C4 photosynthesis, physiological mechanisms underlying variation in stable carbon isotope discrimination (Δ(13)C) are largely unknown, and genetic components influencing Δ(13)C have not been described. We analyzed a maize (Zea mays) introgression library derived from two elite parents to investigate whether Δ(13)C is under genetic control in this C4 species. High-density genotyping with the Illumina MaizeSNP50 Bead Chip was used for a detailed structural characterization of 89 introgression lines. Phenotypic analyses were conducted in the field and in the greenhouse for kernel Δ(13)C as well as plant developmental and photosynthesis-related traits. Highly heritable significant genetic variation for Δ(13)C was detected under field and greenhouse conditions. For several introgression library lines, Δ(13)C values consistently differed from the recurrent parent within and across the two phenotyping platforms. Δ(13)C was significantly associated with 22 out of 164 analyzed genomic regions, indicating a complex genetic architecture of Δ(13)C. The five genomic regions with the largest effects were located on chromosomes 1, 2, 6, 7, and 9 and explained 55% of the phenotypic variation for Δ(13)C. Plant development stage had no effect on Δ(13)C expression, as phenotypic as well as genotypic correlations between Δ(13)C, flowering time, and plant height were not significant. To our knowledge, this is the first study demonstrating Δ(13)C to be under polygenic control in the C4 species maize.

Development and evaluation of single-nucleotide polymorphism markers in allotetraploid rapeseed (Brassica napus L.).

Single-nucleotide polymorphisms (SNPs) and insertion-deletions (INDELs) are currently the important classes of genetic markers for major crop species. In this study, methods for developing SNP markers in rapeseed (Brassica napus L.) and their in silico mapping and use for genotyping are demonstrated. For the development of SNP and INDEL markers, 181 fragments from 121 different gene sequences spanning 86 kb were examined. A combination of different selection methods (genome-specific amplification, hetero-duplex analysis and sequence analysis) allowed the detection of 18 singular fragments that showed a total of 87 SNPs and 6 INDELs between 6 different rapeseed varieties. The average frequency of sequence polymorphism was estimated to be one SNP every 247 bp and one INDEL every 3,583 bp. Most SNPs and INDELs were found in non-coding regions. Polymorphism information content values for SNP markers ranged between 0.02 and 0.50 in a set of 86 varieties. Using comparative genetics data for B. napus and Arabidopsis thaliana, an allocation of SNP markers to linkage groups in rapeseed was achieved: a unique location was determined for seven gene sequences; two and three possible locations were found for six and four sequences, respectively. The results demonstrate the usefulness of existing genomic resources for SNP discovery in rapeseed.