Genetic diversity and core collection development in safflower using genome-wide SNPs

Safflower ( Carthamus tinctorius L.) is an important oilseed crop valued for its high-quality oil, medicinal properties, and resilience to abiotic stresses. Effective utilization of safflower genetic resources is crucial for crop improvement. Developing a representative core collection and employing genomic tools enable efficient characterization, management, and exploitation of the available genetic diversity, thereby accelerating safflower breeding and improvement efforts. This study aimed to characterize the genetic diversity of 5,000 safflower germplasm conserved at the Indian National Genebank using genotyping-by-sequencing and develop a core collection representing the diversity of the entire collection. Comprehensive analyses, including principal component analysis, population structure, and genetic diversity assessments, were conducted to elucidate genetic relationships and ensure optimal representation of diversity within the core set. Double-digest restriction-site associated DNA sequencing (ddRADseq) generated over 21 billion reads, of which high quality reads were retained for analysis. High quality reads were aligned to the safflower reference genome, resulting in the identification of 55,108 high-quality biallelic SNPs. The Core Hunter algorithm was employed to select a core collection of 400 accessions. Principal component analysis revealed limited clustering of accessions based on genetic differentiation or geographical location. Population structure analysis indicated an optimal number of 16 subpopulations for both the safflower germplasm and core collection. The core collection exhibited higher gene diversity (0.38) and polymorphic information content (0.31) values compared to the entire safflower germplasm. A subset of 701 highly informative SNPs was identified for DNA fingerprinting of the core accessions. The development of this core collection provides a valuable resource for efficient safflower genetic diversity conservation, trait discovery, and breeding programs.