Nei and Li developed a mathematical model to study genetic variation in mitochondrial DNA (mtDNA) using restriction endonucleases. The model estimates the number of nucleotide substitutions between populations or species and introduces the concept of "nucleotide diversity" to measure genetic polymorphism at the nucleotide level. They analyzed how restriction sites in mtDNA change over time, considering both the disappearance of original sites and the formation of new ones. The number of restriction sites is influenced by the G+C content and nucleotide substitution rates. The model assumes that nucleotide substitutions occur randomly and follows a Poisson process. The expected number of restriction sites is calculated based on the probability of a specific sequence being present in the DNA. The variance of the number of restriction sites is derived from the binomial and Poisson distributions. The study also examines DNA divergence between two populations, considering the number of shared restriction sites and the proportion of shared DNA fragments. The authors derived formulas to estimate the number of nucleotide substitutions per site (δ) based on the proportion of shared sites (S) or fragments (F). These formulas are compared with previous studies, and the authors suggest that the estimate of δ can be derived from S or F using specific equations. The accuracy of these estimates is tested through a computer simulation, where artificial DNA sequences are generated and analyzed to assess the performance of the formulas. The authors also discuss the importance of accounting for intrapopulational variation when estimating genetic divergence between closely related species. They propose a method to correct for this variation by subtracting the average nucleotide differences within populations from the total interpopulational differences. The concept of nucleotide diversity (π) is introduced as a measure of genetic variation within a population, defined as the average number of nucleotide differences between two randomly chosen DNA sequences. The study highlights the importance of considering nucleotide diversity in estimating genetic divergence, especially in closely related species. The results suggest that mtDNA is more variable than nuclear DNA in some cases, which has implications for understanding genetic diversity in different organisms.Nei and Li developed a mathematical model to study genetic variation in mitochondrial DNA (mtDNA) using restriction endonucleases. The model estimates the number of nucleotide substitutions between populations or species and introduces the concept of "nucleotide diversity" to measure genetic polymorphism at the nucleotide level. They analyzed how restriction sites in mtDNA change over time, considering both the disappearance of original sites and the formation of new ones. The number of restriction sites is influenced by the G+C content and nucleotide substitution rates. The model assumes that nucleotide substitutions occur randomly and follows a Poisson process. The expected number of restriction sites is calculated based on the probability of a specific sequence being present in the DNA. The variance of the number of restriction sites is derived from the binomial and Poisson distributions. The study also examines DNA divergence between two populations, considering the number of shared restriction sites and the proportion of shared DNA fragments. The authors derived formulas to estimate the number of nucleotide substitutions per site (δ) based on the proportion of shared sites (S) or fragments (F). These formulas are compared with previous studies, and the authors suggest that the estimate of δ can be derived from S or F using specific equations. The accuracy of these estimates is tested through a computer simulation, where artificial DNA sequences are generated and analyzed to assess the performance of the formulas. The authors also discuss the importance of accounting for intrapopulational variation when estimating genetic divergence between closely related species. They propose a method to correct for this variation by subtracting the average nucleotide differences within populations from the total interpopulational differences. The concept of nucleotide diversity (π) is introduced as a measure of genetic variation within a population, defined as the average number of nucleotide differences between two randomly chosen DNA sequences. The study highlights the importance of considering nucleotide diversity in estimating genetic divergence, especially in closely related species. The results suggest that mtDNA is more variable than nuclear DNA in some cases, which has implications for understanding genetic diversity in different organisms.