BackgroundDent 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.ResultsWe 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.ConclusionsIn 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.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-016-1009-x) contains supplementary material, which is available to authorized users.

In plants with C 4 photosynthesis, physiological mechanisms underlying variation in stable carbon isotope discrimination (D 13 C) are largely unknown, and genetic components influencing D 13 C have not been described. We analyzed a maize (Zea mays) introgression library derived from two elite parents to investigate whether D 13C is under genetic control in this C 4 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 D 13C as well as plant developmental and photosynthesis-related traits. Highly heritable significant genetic variation for D 13C was detected under field and greenhouse conditions. For several introgression library lines, D 13C values consistently differed from the recurrent parent within and across the two phenotyping platforms. D 13C was significantly associated with 22 out of 164 analyzed genomic regions, indicating a complex genetic architecture of D 13C. 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 D In C 3 plants, the important steps of CO 2 uptake include the diffusion of atmospheric CO 2 through the boundary layer and the stomata. Subsequently, CO 2 is taken up by the cell and enters the chloroplast, where carboxylation by Rubisco takes place. During photosynthetic carbon fixation, the strongest fractionation of carbon isotopes occurs during the carboxylation reaction of Rubisco (Roeske and O'Leary, 1984). A theoretical model of D 13 C in C 3 photosynthesis has been described by Farquhar et al. (1982), in which D 13 C depends linearly on the ratio of intercellular to ambient partial pressure of CO 2 (p i p a 21 ), and thus provides an indication of stomatal conductance and photosynthetic capacity. Additionally, the model includes the dependency of D 13C on the fractionation of carbon isotopes during CO 2 diffusion in the air and on the enzymatic properties of the Rubisco enzyme.For rice (Oryza sativa), tomato (Solanum lycopersicum), and wheat (Triticum aestivum), it has been shown that genetic variation for D 13C is quantitative, genotype-byenvironment interaction is small, and the trait heritability is high (Condon and Richards, 1992;Rebetzke et al., 2002;Comstock et al., 2005;Impa et al., 2005). Quantitative trait

The objectives of this research were to establish a practicable phenotyping platform for assessing the drought stress response of perennial ryegrass (Lolium perenne L.; Lp), and to use this platform for evaluating the variation for drought tolerance among a panel of 39 diverse Lp populations. A moderate‐to‐strong correlation was assessed between the performance of plants grown in a hydroponics system, where the stress was generated by the addition of polyethylene glycol (PEG), and those grown in the field in a rainout shelter. Following the application of drought stress, tetraploid Lp populations, along with a small number of reference Festulolium and Festuca sp. accessions, were able to develop more shoot and root dry matter than diploid Lp populations. The onset of drought symptoms was also delayed within these accessions and the plants recovered better once drought had been relieved. Although most of the diploid Lp populations were drought susceptible, there was a considerable accession‐to‐accession variation for performance under drought stress conditions. Measuring biomass production and post‐drought recovery in rainout shelter experiments in combination with the assessment of root biomass accumulation in PEG‐supplemented hydroponics represented a viable means of screening Lp germplasm for drought tolerance.

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.