The evolutionary distance between a pair of sequences usually is measured by the number of nucleotide (or amino acid) substitutions occurring between them. Evolutionary distances are fundamental for the study of molecular evolution and are useful for phylogenetic reconstructions and the estimation of divergence times. Most of the widely used methods for distance estimation for nucleotide and amino acid sequences are included in MEGA. In the following three sections, we present a brief discussion of these methods: nucleotide substitutions, synonymous-nonsynonymous substitutions, and amino acid substitutions. Further details of these methods and general guidelines for the use of these methods are given in Nei and Kumar (2000) . Note that in addition to the distance estimates, MEGA also computes the standard errors of the estimates using the analytical formulas and the bootstrap method .
Distance methods included in MEGA in divided in three categories (Nucleotide, Syn-nonsynonymous, and Amino acid):
Nucleotide
Sequences are compared nucleotide-by-nucleotide. These distances can be computed for protein coding and non-coding nucleotide sequences.
Jukes-Cantor Model
with Rate Uniformity Among Sites
with Rate Variation Among Sites
Tajima-Nei Model
with Rate Uniformity and Pattern Homogeneity
with Rate Variation Among Sites
with Pattern Heterogeneity Between Lineages
with Rate Variation and Pattern Heterogeneity
Kimura 2-Parameter Model
with Rate Variation Among Sites
Tamura 3-Parameter Model
with Rate Uniformity and Pattern Homogeneity
with Rate Variation Among Sites
with Pattern Heterogeneity Between Lineages
with Rate Variation and Pattern Heterogeneity
Tamura-Nei Model
With Rate Uniformity and Pattern Homogeneity
with Rate Variation Among Sites
with Pattern Heterogeneity Between Lineages
with Rate Variation and Pattern Heterogeneity
Log-Det Method
with Pattern Heterogeneity Between Lineages
Maximum Composite Likelihood Model
with Rate Uniformity and Pattern Homogeneity
with Rate Variation Among Sites
with Pattern Heterogeneity Between Lineages
with Rate Variation and Pattern Heterogeneity