Association studies are the choice approach in the discovery of the genomic basis of complex traits. To carry out such analysis, researchers frequently need to (1) select optimally informative sets of Single Nucleotide Polymorphisms (SNPs) in candidate regions and (2) annotate the results of associations found by means of genome-wide SNP arrays. These are complex tasks, since many criteria have to be considered, including the SNPs' functional properties, technological information and haplotype frequencies in given populations. SYSNPs implements algorithms that allow for efficient and simultaneous consideration of all the relevant criteria to obtain sets of SNPs that properly cover arbitrarily large lists of genes or genomic regions. Complementarily, SYSNPs allows for comprehensive functional annotation of SNPs linked to any given marker SNP. SYSNPs dramatically reduces the effort needed for SNP selection from days of searching various databases to a few minutes using a simple browser.