Background: The recent sequencing of full genomes has led to the availability of many SNP markers which are very useful for the mapping of complex traits. In livestock production, there are still no commercial arrays and many studies use home-made sets of SNPs. Thus, the current methodologies for SNP genotyping are still expensive and it is a crucial step to select the SNPs to use. Indeed, the main factors affecting the power of the linkage analyses are the density of the genetic map and the heterozygosity of markers in tested animal parents. Findings: This is why we have developed a PERL program selecting a defined number of markers based on their locations on the genome and their informativity in specific experimental designs. As an option, different experimental designs can be combined in order to select the best possible common marker set. The program has been tested using different conditions of marker informativity and density with both real and simulated datasets. The results show the efficiency of our program to select the most informative markers even if there is a wide range of informativity for whole genome scan mapping analyses. In case of combination of different experimental crosses, the multidesign mode can optimize the SNP markers selection. Conclusion: Written in PERL, it assures a maximum portability to other operating systems (OS) and the source code availability for user modifications. Except for the simulation mode which could be time consuming, MarkerSet can compute results in a very short time.