BSTA: a targeted approach combines bulked segregant analysis with next-generation sequencing and de novo transcriptome assembly for SNP discovery in sunflower

Background: Sunflower belongs to the largest plant family on earth, the genomically poorly explored Compositae. Downy mildew Plasmopara halstedii (Farlow) Berlese & de Toni is one of the major diseases of cultivated sunflower (Helianthus annuus L.). In the search for new sources of downy mildew resistance, the locus Pl(ARG) on linkage group 1 (LG1) originating from H. argophyllus is promising since it confers resistance against all known races of the pathogen. However, the mapping resolution in the Pl(ARG) region is hampered by significantly suppressed recombination and by limited availability of polymorphic markers. Here we examined a strategy developed for the enrichment of molecular markers linked to this specific genomic region. We combined bulked segregant analysis (BSA) with next-generation sequencing (NGS) and de novo assembly of the sunflower transcriptome for single nucleotide polymorphism (SNP) discovery in a sequence resource combining reads originating from two sunflower species, H. annuus and H. argophyllus. Results: A computational pipeline developed for SNP calling and pattern detection identified 219 candidate genes. For a proof of concept, 42 resistance gene-like sequences were subjected to experimental SNP validation. Using a high-resolution mapping population, 12 SNP markers were mapped to LG1. We successfully verified candidate sequences either co-segregating with or closely flanking Pl(ARG). Conclusions: This study is the first successful example to improve bulked segregant analysis with de novo transcriptome assembly using next generation sequencing. The BSTA pipeline we developed provides a useful guide for similar studies in other non-model organisms. Our results demonstrate this method is an efficient way to enrich molecular markers and to identify candidate genes in a specific mapping interval.