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Showing posts with the label evolutionary analysis

Phylogenetics Support Tyrannosaurus Rex's Evolutionary Relationship with Birds

Tyrannosaurus rex peptide sequences are more similar to modern-day birds than to reptiles, according to new research, providing added evidence for a relatively close evolutionary relationship between dinosaurs and birds. About a year ago, researchers from Harvard University and elsewhere first reported that they could tease minuscule amounts of protein from mastodon and T. rex bone samples that were up to 600,000 and 68 million-years-old, respectively, and analyze them by mass spectrometry. Now, members of the same team report using molecular phylogenetics to group mastodon and T. rex based on their collagen protein peptide sequences. These latest results , appearing in today’s issue of Science , suggest T. rex is more closely related to chickens and ostriches than to alligators and seem to confirm the long-held suspicion that dinosaurs and birds have a common ancestor. They also corroborate a relationship between mastodons and modern day elephants. for more

MEGA: A biologist-centric software for evolutionary analysis of DNA and protein sequences

The Molecular Evolutionary Genetics Analysis ( MEGA ) software is a desktop application designed for comparative analysis of homologous gene sequences either from multigene families or from different species with a special emphasis on inferring evolutionary relationships and patterns of DNA and protein evolution. In addition to the tools for statistical analysis of data, MEGA provides many convenient facilities for the assembly of sequence data sets from files or web-based repositories, and it includes tools for visual presentation of the results obtained in the form of interactive phylogenetic trees and evolutionary distance matrices. Here we discuss the motivation, design principles and priorities that have shaped the development of MEGA. We also discuss how MEGA might evolve in the future to assist researchers in their growing need to analyze large data set using new computational methods.