The free-living nematode Pristionchus pacificus is one of several species that have recently been developed as a satellite system for comparative functional studies in evolutionary developmental biology. Comparisons of developmental processes between P. pacificus and the well established model organism Caenorhabditis elegans at the cellular and genetic levels provide detailed insight into the molecular changes that shape evolutionary transitions. To facilitate genetic analysis and cloning of mutations in P. pacificus, we previously generated a BAC-based genetic linkage map for this organism. Here, we describe the construction of a physical map of the P. pacificus genome based on AFLP fingerprint analysis of 7747 BAC clones. Most of the SSCP markers used to generate the genetic linkage map were derived from BAC ends, so that the physical genome map and the genetic map can be integrated. The contigs that make up the physical map are evenly distributed over the genetic linkage map and no clustering is observed, indicating that the physical map provides a valid representation of the P. pacificus genome. The integrated genome map thus provides a framework for positional cloning and the study of genome evolution in nematodes.

ORCID IDs: 0000-0002-9014-9516 (D.V.); 0000-0001-8918-0711 (J.J.B.K.).Quantitative traits in plants are controlled by a large number of genes and their interaction with the environment. To disentangle the genetic architecture of such traits, natural variation within species can be explored by studying genotype-phenotype relationships. Genome-wide association studies that link phenotypes to thousands of single nucleotide polymorphism markers are nowadays common practice for such analyses. In many cases, however, the identified individual loci cannot fully explain the heritability estimates, suggesting missing heritability. We analyzed 349 Arabidopsis accessions and found extensive variation and high heritabilities for different morphological traits. The number of significant genome-wide associations was, however, very low. The application of genomic prediction models that take into account the effects of all individual loci may greatly enhance the elucidation of the genetic architecture of quantitative traits in plants. Here, genomic prediction models revealed different genetic architectures for the morphological traits. Integrating genomic prediction and association mapping enabled the assignment of many plausible candidate genes explaining the observed variation. These genes were analyzed for functional and sequence diversity, and good indications that natural allelic variation in many of these genes contributes to phenotypic variation were obtained. For ACS11, an ethylene biosynthesis gene, haplotype differences explaining variation in the ratio of petiole and leaf length could be identified.The natural phenomena of mutation and recombination that change the genetic code with each generation have given rise to the enormous genetic diversity between and within species. Through evolutionary processes, such as drift, migration, and selection, plants have accumulated a vast number of molecular polymorphisms that enabled adaptation to a wide range of environments (Kooke and Keurentjes, 2012). With the recent advancements in genetic and genomic tools, this nucleotide diversity can be fully surveyed to identify causal polymorphisms for many different plant phenotypes. This should allow the identification of molecular changes that provided evolutionary advantages and beneficial characteristics in agronomically important traits.Through selection on variation in performance, plants have adapted to different environments. Plant performance is directly determined by life history traits, such as flowering time and growth rate, which in turn depend on genetics, morphology, physiology, and the environment (Roff, 2007;Kooke et al., 2015). Understanding the regulation of plant growth and morphology is therefore essential for the comprehension of plant performance. Arabidopsis has adapted to a wide range of environments and displays an extensive variety in morphological and growth-related phenotypes. Its small genome size, the publicly available

Genomic selection offers several routes for increasing the genetic gain or efficiency of plant breeding programmes. In various species of livestock, there is empirical evidence of increased rates of genetic gain from the use of genomic selection to target different aspects of the breeder’s equation. Accurate predictions of genomic breeding value are central to this, and the design of training sets is in turn central to achieving sufficient levels of accuracy. In summary, small numbers of close relatives and very large numbers of distant relatives are expected to enable predictions with higher accuracy. To quantify the effect of some of the properties of training sets on the accuracy of genomic selection in crops, we performed an extensive field-based winter wheat trial. In summary, this trial involved the construction of 44 F 2:4 bi- and tri-parental populations, from which 2992 lines were grown on four field locations and yield was measured. For each line, genotype data were generated for 25 K segregating SNP markers. The overall heritability of yield was estimated to 0.65, and estimates within individual families ranged between 0.10 and 0.85. Genomic prediction accuracies of yield BLUEs were 0.125–0.127 using two different cross-validation approaches and generally increased with training set size. Using related crosses in training and validation sets generally resulted in higher prediction accuracies than using unrelated crosses. The results of this study emphasise the importance of the training panel design in relation to the genetic material to which the resulting prediction model is to be applied. Electronic supplementary material The online version of this article (10.1007/s00122-019-03327-y) contains supplementary material, which is available to authorized users.

The Bovini species comprise both domestic and wild cattle species. Published phylogenies of this tribe based on mitochondrial DNA contain anomalies, while nuclear sequences show only low variation. We have used amplified fragment length polymorphism (AFLP) fingerprinting in order to detect variation in loci distributed over the nuclear genome. Computer-assisted scoring of electrophoretic fingerprinting patterns yielded 361 markers, which provided sufficient redundancy to suppress stochastic effects of intraspecies polymorphisms and length homoplasies (comigration of nonhomologous fragments). Tree reconstructions reveal three clusters: African buffalo with water buffalo, ox with zebu, and