MEGA is a biologist-centric software for evolutionary analysis of DNA and protein sequences. Developed by Sudhir Kumar, Masatoshi Nei, Joel Dudley, and Koichiro Tamura, MEGA is a desktop application designed for comparative analysis of homologous gene sequences, with a focus on inferring evolutionary relationships and patterns of DNA and protein evolution. It provides tools for statistical analysis, sequence data assembly, and visual presentation of results in the form of phylogenetic trees and distance matrices. MEGA was developed to address the need for user-friendly software that allows biologists to apply computational and statistical methods to understand gene and species function, evolution, and adaptation. The software evolved from the authors' own need for statistical methods in phylogenetic analysis in the early 1990s. Initially, MEGA was a character-based program for DOS systems, offering methods for estimating evolutionary distances and phylogenetic inference. Over time, it transitioned to a graphical user interface (GUI) for Windows, enabling more sophisticated data manipulation and analysis. MEGA 1, released in 1993, was widely adopted by biologists, leading to the development of MEGA 2 in 2001, which further improved capabilities for analyzing larger datasets. MEGA 3, released in 2004, addressed the need for easier sequence data retrieval and alignment. MEGA 4, released in 2007, introduced features such as detailed captions for results, maximum composite likelihood methods, and Linux support via Wine. MEGA 5 and beyond aim to expand the software's capabilities, including the use of maximum likelihood methods for comparative genomics, integration of bioinformatics tools, and development as a cross-platform web application. MEGA is designed with a biologist-centric approach, emphasizing user-friendliness, context-dependence, and intuitive data assembly. It includes features for saving user sessions, transparency of assumptions, and detailed explanations of results. The software has become a widely used tool in the field of molecular evolutionary genetics, with a growing number of citations and users. MEGA's success highlights the importance of user-friendly, biologist-centric software in the analysis of large datasets and the interpretation of evolutionary patterns.MEGA is a biologist-centric software for evolutionary analysis of DNA and protein sequences. Developed by Sudhir Kumar, Masatoshi Nei, Joel Dudley, and Koichiro Tamura, MEGA is a desktop application designed for comparative analysis of homologous gene sequences, with a focus on inferring evolutionary relationships and patterns of DNA and protein evolution. It provides tools for statistical analysis, sequence data assembly, and visual presentation of results in the form of phylogenetic trees and distance matrices. MEGA was developed to address the need for user-friendly software that allows biologists to apply computational and statistical methods to understand gene and species function, evolution, and adaptation. The software evolved from the authors' own need for statistical methods in phylogenetic analysis in the early 1990s. Initially, MEGA was a character-based program for DOS systems, offering methods for estimating evolutionary distances and phylogenetic inference. Over time, it transitioned to a graphical user interface (GUI) for Windows, enabling more sophisticated data manipulation and analysis. MEGA 1, released in 1993, was widely adopted by biologists, leading to the development of MEGA 2 in 2001, which further improved capabilities for analyzing larger datasets. MEGA 3, released in 2004, addressed the need for easier sequence data retrieval and alignment. MEGA 4, released in 2007, introduced features such as detailed captions for results, maximum composite likelihood methods, and Linux support via Wine. MEGA 5 and beyond aim to expand the software's capabilities, including the use of maximum likelihood methods for comparative genomics, integration of bioinformatics tools, and development as a cross-platform web application. MEGA is designed with a biologist-centric approach, emphasizing user-friendliness, context-dependence, and intuitive data assembly. It includes features for saving user sessions, transparency of assumptions, and detailed explanations of results. The software has become a widely used tool in the field of molecular evolutionary genetics, with a growing number of citations and users. MEGA's success highlights the importance of user-friendly, biologist-centric software in the analysis of large datasets and the interpretation of evolutionary patterns.