Abstract
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.
Highlights
Sunflower (Helianthus annuus L) is a member of the Asteraceae family, and is the fourth most economically important annual crop grown worldwide for edible oil [1]
We report and validate a marker linked to a rust resistance gene, R12, in the constructed consensus map
Three F2 mapping populations were developed using five parental lines of cultivated sunflower, four of which were used in the initial restriction site associated DNA (RAD) sequencing step
Summary
Sunflower (Helianthus annuus L) is a member of the Asteraceae family, and is the fourth most economically important annual crop grown worldwide for edible oil [1]. Molecular markers and high density genetic linkage maps are important tools for understanding genome organization, and can facilitate comparative genomics, marker-assisted selection (MAS), identification of marker-trait associations via linkage or association mapping analysis, and isolation of genes by map-based cloning [3,4]. Association mapping and genomic selection are dependent on a large number of polymorphic markers. These analyses are only successful if thousands of markers are available, because of the low level of linkage disequilibrium (LD) present in germplasm resources of sunflower [32,33,34,35]. When large numbers of markers are employed in an analysis, especially for routine breeding purposes such as genomic selection, the marker must be high-throughput and cost effective to provide timely and repeatable data
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