A high-density SNP Map of sunflower derived from RAD-sequencing facilitating fine-mapping of the rust resistance gene R12.

A high-resolution genetic map of sunflower was constructed by integrating SNP data from three F2 mapping populations (HA 89/RHA 464, B-line/RHA 464, and CR 29/RHA 468). The consensus map spanned a total length of 1443.84 cM, and consisted of 5,019 SNP markers derived from RAD tag sequencing and 118 publicly available SSR markers distributed in 17 linkage groups, corresponding to the haploid chromosome number of sunflower. The maximum interval between markers in the consensus map is 12.37 cM and the average distance is 0.28 cM between adjacent markers. Despite a few short-distance inversions in marker order, the consensus map showed high levels of collinearity among individual maps with an average Spearman's rank correlation coefficient of 0.972 across the genome. The order of the SSR markers on the consensus map was also in agreement with the order of the individual map and with previously published sunflower maps. Three individual and one consensus maps revealed the uneven distribution of markers across the genome. Additionally, we performed fine mapping and marker validation of the rust resistance gene R12, providing closely linked SNP markers for marker-assisted selection of this gene in sunflower breeding programs. This high resolution consensus map will serve as a valuable tool to the sunflower community for studying marker-trait association of important agronomic traits, marker assisted breeding, map-based gene cloning, and comparative mapping.

De novo sequencing of sunflower genome for SNP discovery using RAD (Restriction site Associated DNA) approach.

BACKGROUND: Application of Single Nucleotide Polymorphism (SNP) marker technology as a tool in sunflower breeding programs offers enormous potential to improve sunflower genetics, and facilitate faster release of sunflower hybrids to the market place. Through a National Sunflower Association (NSA) funded initiative, we report on the process of SNP discovery through reductive genome sequencing and local assembly of six diverse sunflower inbred lines that represent oil as well as confection types. RESULTS: A combination of Restriction site Associated DNA Sequencing (RAD-Seq) protocols and Illumina paired-end sequencing chemistry generated high quality 89.4 M paired end reads from the six lines which represent 5.3 GB of the sequencing data. Raw reads from the sunflower line, RHA 464 were assembled de novo to serve as a framework reference genome. About 15.2 Mb of sunflower genome distributed over 42,267 contigs were obtained upon assembly of RHA 464 sequencing data, the contig lengths ranged from 200 to 950 bp with an N50 length of 393 bp. SNP calling was performed by aligning sequencing data from the six sunflower lines to the assembled reference RHA 464. On average, 1 SNP was located every 143 bp of the sunflower genome sequence. Based on several filtering criteria, a final set of 16,467 putative sequence variants with characteristics favorable for Illumina Infinium Genotyping Technology (IGT) were mined from the sequence data generated across six diverse sunflower lines. CONCLUSION: Here we report the molecular and computational methodology involved in SNP development for a complex genome like sunflower lacking reference assembly, offering an attractive tool for molecular breeding purposes in sunflower.