ORCID ID: 0000-0003-3011-8731 (N.S.).Rye (Secale cereale) is closely related to wheat (Triticum aestivum) and barley (Hordeum vulgare). Due to its large genome (;8 Gb) and its regional importance, genome analysis of rye has lagged behind other cereals. Here, we established a virtual linear gene order model (genome zipper) comprising 22,426 or 72% of the detected set of 31,008 rye genes. This was achieved by high-throughput transcript mapping, chromosome survey sequencing, and integration of conserved synteny information of three sequenced model grass genomes (Brachypodium distachyon, rice [Oryza sativa], and sorghum [Sorghum bicolor]). This enabled a genome-wide high-density comparative analysis of rye/barley/model grass genome synteny. Seventeen conserved syntenic linkage blocks making up the rye and barley genomes were defined in comparison to model grass genomes. Six major translocations shaped the modern rye genome in comparison to a putative Triticeae ancestral genome. Strikingly dissimilar conserved syntenic gene content, gene sequence diversity signatures, and phylogenetic networks were found for individual rye syntenic blocks. This indicates that introgressive hybridizations (diploid or polyploidy hybrid speciation) and/or a series of whole-genome or chromosome duplications played a role in rye speciation and genome evolution.

From simulation studies it is known that the allocation of experimental resources has a crucial effect on power of QTL detection as well as on accuracy and precision of QTL estimates. In this study, we used a very large experimental data set composed of 976 F 5 maize testcross progenies evaluated in 19 environments and cross-validation to assess the effect of sample size (N ), number of test environments (E ), and significance threshold on the number of detected QTL, the proportion of the genotypic variance explained by them, and the corresponding bias of estimates for grain yield, grain moisture, and plant height. In addition, we used computer simulations to compare the usefulness of two cross-validation schemes for obtaining unbiased estimates of QTL effects. The maximum, validated genotypic variance explained by QTL in this study was 52.3% for grain moisture despite the large number of detected QTL, thus confirming the infinitesimal model of quantitative genetics. In both simulated and experimental data, the effect of sample size on power of QTL detection as well as on accuracy and precision of QTL estimates was large. The number of detected QTL and the proportion of genotypic variance explained by QTL generally increased more with increasing N than with increasing E. The average bias of QTL estimates and its range were reduced by increasing N and E. Cross-validation performed well with respect to yielding asymptotically unbiased estimates of the genotypic variance explained by QTL. On the basis of our findings, recommendations for planning of QTL mapping experiments and allocation of experimental resources are given.

Heterosis is widely used in breeding, but the genetic basis of this biological phenomenon has not been elucidated. We postulate that additive and dominance genetic effects as well as two-locus interactions estimated in classical QTL analyses are not sufficient for quantifying the contributions of QTL to heterosis. A general theoretical framework for determining the contributions of different types of genetic effects to heterosis was developed. Additive 3 additive epistatic interactions of individual loci with the entire genetic background were identified as a major component of midparent heterosis. On the basis of these findings we defined a new type of heterotic effect denoted as augmented dominance effect d i * that comprises the dominance effect at each QTL minus half the sum of additive 3 additive interactions with all other QTL. We demonstrate that genotypic expectations of QTL effects obtained from analyses with the design III using testcrosses of recombinant inbred lines and composite-interval mapping precisely equal genotypic expectations of midparent heterosis, thus identifying genomic regions relevant for expression of heterosis. The theory for QTL mapping of multiple traits is extended to the simultaneous mapping of newly defined genetic effects to improve the power of QTL detection and distinguish between dominance and overdominance.

The limited population sizes used in many quantitative trait locus (QTL) detection experiments can lead to underestimation of QTL number, overestimation of QTL effects, and failure to quantify QTL interactions. We used the barley/barley stripe rust pathosystem to evaluate the effect of population size on the estimation of QTL parameters. We generated a large (n = 409) population of doubled haploid lines derived from the cross of two inbred lines, BCD47 and Baronesse. This population was evaluated for barley stripe rust severity in the Toluca Valley, Mexico, and in Washington State, USA, under field conditions. BCD47 was the principal donor of resistance QTL alleles, but the susceptible parent also contributed some resistance alleles. The major QTL, located on the long arm of chromosome 4H, close to the Mlo gene, accounted for up to 34% of the phenotypic variance. Subpopulations of different sizes were generated using three methods-resampling, selective genotyping, and selective phenotyping-to evaluate the effect of population size on the estimation of QTL parameters. In all cases, the number of QTL detected increased with population size. QTL with large effects were detected even in small populations, but QTL with small effects were detected only by increasing population size. Selective genotyping and/or selective phenotyping approaches could be effective strategies for reducing the costs associated with conducting QTL analysis in large populations. The method of choice will depend on the relative costs of genotyping versus phenotyping.

BackgroundThe improvement of agricultural crops with regard to yield, resistance and environmental adaptation is a perpetual challenge for both breeding and research. Exploration of the genetic potential and implementation of genome-based breeding strategies for efficient rye (Secale cereale L.) cultivar improvement have been hampered by the lack of genome sequence information. To overcome this limitation we sequenced the transcriptomes of five winter rye inbred lines using Roche/454 GS FLX technology.ResultsMore than 2.5 million reads were assembled into 115,400 contigs representing a comprehensive rye expressed sequence tag (EST) resource. From sequence comparisons 5,234 single nucleotide polymorphisms (SNPs) were identified to develop the Rye5K high-throughput SNP genotyping array. Performance of the Rye5K SNP array was investigated by genotyping 59 rye inbred lines including the five lines used for sequencing, and five barley, three wheat, and two triticale accessions. A balanced distribution of allele frequencies ranging from 0.1 to 0.9 was observed. Residual heterozygosity of the rye inbred lines varied from 4.0 to 20.4% with higher average heterozygosity in the pollen compared to the seed parent pool.ConclusionsThe established sequence and molecular marker resources will improve and promote genetic and genomic research as well as genome-based breeding in rye.