This transformation also paves the way for development of a MEGA X version for macOS in the near future. This advancement eliminates the Windows-only limitation of Mega, which has become particularly acute due to the increasing use of Linux in biological research. Therefore, Mega has been transformed into a cross-platform version that runs natively on Linux and Microsoft Windows. 2016), so a more comprehensive solution is required for users of alternate platforms. Emulators cannot be used effectively for the latest 64-bit version of Mega that is built to handle memory-intensive analyses of large contemporary data sets ( Kumar et al. But the ad hoc Windows-emulation solution is sluggish and relatively unstable when compared with the performance in MS Windows. These versions have been downloaded over 200,000 times.
Some of the Mega releases have been packaged for Linux systems using the WINE compatibility layer for POSIX-compliant operating systems and the Wineskin tool (built on WINE) for macOS systems. 1994) and then upgraded for use in MS Windows eight times, including MEGA 1 to MEGA 6 and MEGA-CC and MEGA-MD ( Kumar et al. Mega was first developed for MS DOS in the early 1990s ( Kumar et al.
Over the last 25 years, Mega’s use in evolutionary analysis has been cited in over one hundred thousand studies in diverse biological fields. Mega includes a large repertoire of programs for assembling sequence alignments, inferring evolutionary trees, estimating genetic distances and diversities, inferring ancestral sequences, computing timetrees, and testing selection ( Kumar et al. Molecular Evolutionary Genetics Analysis ( Mega) software provides tools to conduct such analyses.
The numerous steps required to glean interpretable and actionable results from raw sequence data invariably require comparative analysis of molecular sequences to discover functional and adaptive genome differences. Over the past decade, genome sequencing has become an efficient and potent means to investigate a broad array of biological systems, from large-scale studies of biological diversity to tracking the evolution and origin of pathogenic microbes.
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