Simple sequence repeats (SSRs), also known as microsatellites, are highly polymorphic and widely distributed in mammalian genomes. They are important genetic markers used in genetic mapping studies. Mutations in SSRs typically involve small changes in repeat units, but some SSRs show extreme instability. This instability is linked to several human diseases, suggesting that large changes in repeat number also occur. The study introduces a two-phase mutation model to explain these mutational processes. This model assumes that most mutations are single-step changes, but infrequent large jumps in repeat number also occur. The model was tested against data from 10 SSR loci in the Sardinian population, which showed the best fit for most loci. The study also compared SSR data with mitochondrial DNA (mtDNA) data from Egyptian and sub-Saharan African populations, finding that SSRs can be useful in studying population divergence. The results suggest that SSRs can provide similar information about population distances as mtDNA. The study also discusses the implications of these findings for understanding mutational processes in SSRs and their role in human genetic diversity. The two-phase model was found to be a better fit for most SSR loci than the one-step model, indicating that both small and large mutations contribute to SSR variation. The study also highlights the importance of considering demographic history and population growth in understanding SSR mutational processes. The findings support the use of SSRs in studying human genetic diversity and population differentiation.Simple sequence repeats (SSRs), also known as microsatellites, are highly polymorphic and widely distributed in mammalian genomes. They are important genetic markers used in genetic mapping studies. Mutations in SSRs typically involve small changes in repeat units, but some SSRs show extreme instability. This instability is linked to several human diseases, suggesting that large changes in repeat number also occur. The study introduces a two-phase mutation model to explain these mutational processes. This model assumes that most mutations are single-step changes, but infrequent large jumps in repeat number also occur. The model was tested against data from 10 SSR loci in the Sardinian population, which showed the best fit for most loci. The study also compared SSR data with mitochondrial DNA (mtDNA) data from Egyptian and sub-Saharan African populations, finding that SSRs can be useful in studying population divergence. The results suggest that SSRs can provide similar information about population distances as mtDNA. The study also discusses the implications of these findings for understanding mutational processes in SSRs and their role in human genetic diversity. The two-phase model was found to be a better fit for most SSR loci than the one-step model, indicating that both small and large mutations contribute to SSR variation. The study also highlights the importance of considering demographic history and population growth in understanding SSR mutational processes. The findings support the use of SSRs in studying human genetic diversity and population differentiation.