The article by Marie-Pierre Chapuis and Arnaud Estoup investigates the impact of microsatellite null alleles on population differentiation estimates. Microsatellite null alleles, which occur when primer binding sites in flanking regions prevent PCR amplification, are common in populations with large effective sizes and high mutation rates. The authors use computer simulations based on the coalescent model to explore the evolutionary dynamics of null alleles, their effect on genetic differentiation measures like $F_{ST}$ and genetic distances, and the efficiency of null allele frequency estimators. They find that null alleles lead to overestimation of $F_{ST}$ and genetic distances, especially in populations with significant differentiation. The conventional method for correcting genotype data for null alleles is shown to be inaccurate, while a new method proposed by the authors (ENA) for estimating $F_{ST}$ performs well. The ENA method restricts the calculation to visible allele sizes, which are not affected by null alleles. The authors also apply their methods to empirical microsatellite data sets from mosquitoes and bears, confirming the presence and impact of null alleles.The article by Marie-Pierre Chapuis and Arnaud Estoup investigates the impact of microsatellite null alleles on population differentiation estimates. Microsatellite null alleles, which occur when primer binding sites in flanking regions prevent PCR amplification, are common in populations with large effective sizes and high mutation rates. The authors use computer simulations based on the coalescent model to explore the evolutionary dynamics of null alleles, their effect on genetic differentiation measures like $F_{ST}$ and genetic distances, and the efficiency of null allele frequency estimators. They find that null alleles lead to overestimation of $F_{ST}$ and genetic distances, especially in populations with significant differentiation. The conventional method for correcting genotype data for null alleles is shown to be inaccurate, while a new method proposed by the authors (ENA) for estimating $F_{ST}$ performs well. The ENA method restricts the calculation to visible allele sizes, which are not affected by null alleles. The authors also apply their methods to empirical microsatellite data sets from mosquitoes and bears, confirming the presence and impact of null alleles.