Rose is the world’s most important ornamental plant, with economic, cultural and symbolic value. Roses are cultivated worldwide and sold as garden roses, cut flowers and potted plants. Roses are outbred and can have various ploidy levels. Our objectives were to develop a high-quality reference genome sequence for the genus Rosa by sequencing a doubled haploid, combining long and short reads, and anchoring to a high-density genetic map, and to study the genome structure and genetic basis of major ornamental traits. We produced a doubled haploid rose line (‘HapOB’) from Rosa chinensis ‘Old Blush’ and generated a rose genome assembly anchored to seven pseudo-chromosomes (512 Mb with N50 of 3.4 Mb and 564 contigs). The length of 512 Mb represents 90.1–96.1% of the estimated haploid genome size of rose. Of the assembly, 95% is contained in only 196 contigs. The anchoring was validated using high-density diploid and tetraploid genetic maps. We delineated hallmark chromosomal features, including the pericentromeric regions, through annotation of transposable element families and positioned centromeric repeats using fluorescent in situ hybridization. The rose genome displays extensive synteny with the Fragaria vesca genome, and we delineated only two major rearrangements. Genetic diversity was analysed using resequencing data of seven diploid and one tetraploid Rosa species selected from various sections of the genus. Combining genetic and genomic approaches, we identified potential genetic regulators of key ornamental traits, including prickle density and the number of flower petals. A rose APETALA2/TOE homologue is proposed to be the major regulator of petal number in rose. This reference sequence is an important resource for studying polyploidization, meiosis and developmental processes, as we demonstrated for flower and prickle development. It will also accelerate breeding through the development of molecular markers linked to traits, the identification of the genes underlying them and the exploitation of synteny across Rosaceae.

Polyploid organisms carry more than two copies of each chromosome, a condition rarely tolerated in animals but which occurs relatively frequently in the plant kingdom. One of the principal challenges faced by polyploid organisms is to evolve stable meiotic mechanisms to faithfully transmit genetic information to the next generation upon which the study of inheritance is based. In this review we look at the tools available to the research community to better understand polyploid inheritance, many of which have only recently been developed. Most of these tools are intended for experimental populations (rather than natural populations), facilitating genomics-assisted crop improvement and plant breeding. This is hardly surprising given that a large proportion of domesticated plant species are polyploid. We focus on three main areas: (1) polyploid genotyping; (2) genetic and physical mapping; and (3) quantitative trait analysis and genomic selection. We also briefly review some miscellaneous topics such as the mode of inheritance and the availability of polyploid simulation software. The current polyploid analytic toolbox includes software for assigning marker genotypes (and in particular, estimating the dosage of marker alleles in the heterozygous condition), establishing chromosome-scale linkage phase among marker alleles, constructing (short-range) haplotypes, generating linkage maps, performing genome-wide association studies (GWAS) and quantitative trait locus (QTL) analyses, and simulating polyploid populations. These tools can also help elucidate the mode of inheritance (disomic, polysomic or a mixture of both as in segmental allopolyploids) or reveal whether double reduction and multivalent chromosomal pairing occur. An increasing number of polyploids (or associated diploids) are being sequenced, leading to publicly available reference genome assemblies. Much work remains in order to keep pace with developments in genomic technologies. However, such technologies also offer the promise of understanding polyploid genomes at a level which hitherto has remained elusive.

The creation of genetic linkage maps in polyploid species has been a long-standing problem for which various approaches have been proposed. In the case of autopolyploids, a commonly-used simplification is that random bivalents form during meiosis. This leads to relatively straightforward estimation of recombination frequencies using maximum likelihood from which a genetic map can be derived. However, autopolyploids such as tetraploid potato (Solanum tuberosum L.) may exhibit additional features such as double reduction, not normally encountered in diploid or allopolyploid species. In this study we produced a high-density linkage map of tetraploid potato and used it to identify regions of double reduction in a bi-parental mapping population. The frequency of multivalents required to produce this degree of double reduction was determined through simulation. We also determined the effect that multivalents or preferential pairing between homologous chromosomes have on linkage mapping. Low levels of multivalents or preferential pairing do not adversely affect map construction when highly-informative marker types and phases are used. We reveal the double reduction landscape in tetraploid potato, clearly showing that this phenomenon increases with distance from the centromeres.

Intercropping is both a well-established and yet novel agricultural practice, depending on one’s perspective. Such perspectives are principally governed by geographic location and whether monocultural practices predominate. Given the negative environmental effects of monoculture agriculture (loss of biodiversity, reliance on non-renewable inputs, soil degradation, etc.), there has been a renewed interest in cropping systems that can reduce the impact of modern agriculture while maintaining (or even increasing) yields. Intercropping is one of the most promising practices in this regard, yet faces a multitude of challenges if it is to compete with and ultimately replace the prevailing monocultural norm. These challenges include the necessity for more complex agricultural designs in space and time, bespoke machinery, and adapted crop cultivars. Plant breeding for monocultures has focused on maximizing yield in single-species stands, leading to highly productive yet specialized genotypes. However, indications suggest that these genotypes are not the best adapted to intercropping systems. Re-designing breeding programs to accommodate inter-specific interactions and compatibilities, with potentially multiple different intercropping partners, is certainly challenging, but recent technological advances offer novel solutions. We identify a number of such technology-driven directions, either ideotype-driven (i.e., “trait-based” breeding) or quantitative genetics-driven (i.e., “product-based” breeding). For ideotype breeding, plant growth modeling can help predict plant traits that affect both inter- and intraspecific interactions and their influence on crop performance. Quantitative breeding approaches, on the other hand, estimate breeding values of component crops without necessarily understanding the underlying mechanisms. We argue that a combined approach, for example, integrating plant growth modeling with genomic-assisted selection and indirect genetic effects, may offer the best chance to bridge the gap between current monoculture breeding programs and the more integrated and diverse breeding programs of the future.

Polyploid species carry more than two copies of each chromosome, a condition found in many of the world’s most important crops. Genetic mapping in polyploids is more complex than in diploid species, resulting in a lack of available software tools. These are needed if we are to realize all the opportunities offered by modern genotyping platforms for genetic research and breeding in polyploid crops. polymapR is an R package for genetic linkage analysis and integrated genetic map construction from bi-parental populations of outcrossing autopolyploids. It can currently analyse triploid, tetraploid and hexaploid marker datasets and is applicable to various crops including potato, leek, alfalfa, blueberry, chrysanthemum, sweet potato or kiwifruit. It can detect, estimate and correct for preferential chromosome pairing, and has been tested on high-density marker datasets from potato, rose and chrysanthemum, generating high-density integrated linkage maps in all of these crops. polymapR is freely available under the general public license from the Comprehensive R Archive Network (CRAN) at http://cran.r-project.org/package=polymapR. Supplementary data are available at Bioinformatics online.

Summary: It has long been recognised that polyploid species do not always neatly fall into the categories of auto‐ or allopolyploid, leading to the term ‘segmental allopolyploid’ to describe everything in between. The meiotic behaviour of such intermediate species is not fully understood, nor is there consensus as to how to model their inheritance patterns. In this study we used a tetraploid cut rose (Rosa hybrida) population, genotyped using the 68K WagRhSNP array, to construct an ultra‐high‐density linkage map of all homologous chromosomes using methods previously developed for autotetraploids. Using the predicted bivalent configurations in this population we quantified differences in pairing behaviour among and along homologous chromosomes, leading us to correct our estimates of recombination frequency to account for this behaviour. This resulted in the re‐mapping of 25 695 SNP markers across all homologues of the seven rose chromosomes, tailored to the pairing behaviour of each chromosome in each parent. We confirmed the inferred differences in pairing behaviour among chromosomes by examining repulsion‐phase linkage estimates, which also carry information about preferential pairing and recombination. Currently, the closest sequenced relative to rose is Fragaria vesca. Aligning the integrated ultra‐dense rose map with the strawberry genome sequence provided a detailed picture of the synteny, confirming overall co‐linearity but also revealing new genomic rearrangements. Our results suggest that pairing affinities may vary along chromosome arms, which broadens our current understanding of segmental allopolyploidy.