Genetic linkage maps have the potential to facilitate the genetic dissection of complex traits and comparative analyses of genome structure, as well as molecular breeding efforts in species of agronomic importance. Until recently, the majority of such maps was based on relatively low-throughput marker technologies, which limited marker density across the genome. The availability of high-throughput genotyping technologies has, however, made possible the efficient development of high-density genetic maps. Here, we describe the analysis and integration of genotypic data from four sunflower (Helianthus annuus L.) mapping populations to produce a consensus linkage map of the sunflower genome. Although the individual maps (which contained 3500–5500 loci each) were highly colinear, we observed localized variation in recombination rates in several genomic regions. We also observed several gaps up to 26 cM in length that completely lacked mappable markers in individual crosses, presumably due to regions of identity by descent in the mapping parents. Because these regions differed by cross, the consensus map of 10,080 loci contained no such gaps, clearly illustrating the value of simultaneously analyzing multiple mapping populations.

Recent advances in next-generation DNA sequencing technologies have made possible the development of high-throughput SNP genotyping platforms that allow for the simultaneous interrogation of thousands of single-nucleotide polymorphisms (SNPs). Such resources have the potential to facilitate the rapid development of high-density genetic maps, and to enable genome-wide association studies as well as molecular breeding approaches in a variety of taxa. Herein, we describe the development of a SNP genotyping resource for use in sunflower (Helianthus annuus L.). This work involved the development of a reference transcriptome assembly for sunflower, the discovery of thousands of high quality SNPs based on the generation and analysis of ca. 6 Gb of transcriptome re-sequencing data derived from multiple genotypes, the selection of 10,640 SNPs for inclusion in the genotyping array, and the use of the resulting array to screen a diverse panel of sunflower accessions as well as related wild species. The results of this work revealed a high frequency of polymorphic SNPs and relatively high level of cross-species transferability. Indeed, greater than 95% of successful SNP assays revealed polymorphism, and more than 90% of these assays could be successfully transferred to related wild species. Analysis of the polymorphism data revealed patterns of genetic differentiation that were largely congruent with the evolutionary history of sunflower, though the large number of markers allowed for finer resolution than has previously been possible.

The Compositae is one of the largest and most economically important families of flowering plants and includes a diverse array of food crops, horticultural crops, medicinals, and noxious weeds. Despite its size and economic importance, there is no reference genome sequence for the Compositae, which impedes research and improvement efforts. We report on progress toward sequencing the 3.5 Gb genome of cultivated sunflower ( Helianthus annuus ), the most important crop in the family. Our sequencing strategy combines whole-genome shotgun sequencing using the Solexa and 454 platforms with the generation of high-density genetic and physical maps that serve as scaffolds for the linear assembly of whole-genome shotgun sequences. The performance of this approach is enhanced by the construction of a sequence-based physical map, which provides unique sequence-based tags every 5–6 kb across the genome. Thus far, our physical map covers ∼85% of the sunflower genome, and we have generated ∼80× genome coverage with Solexa reads and 15.5× with 454 reads. Preliminary analyses indicated that ∼78% of the sunflower genome consists of repetitive sequences. Nonetheless, ∼76% of contigs >5 kb in size can be assigned to either the physical or genetic map or to both, suggesting that our approach is likely to deliver a highly accurate and contiguous reference genome for sunflower.