From echolocation in bats and dolphins to the ability to fly, found in both birds and insects, convergent evolution – or the independent emergence of similar traits in unrelated species – has long been of interest to the scientific community.
The repeated emergence of the same functional trait provides the opportunity to investigate how genes and proteins relate to this process. Traditional investigation methods examine small sequence similarities rather than complex differences, such as 3D structure.
With the help of an advanced AI protein language model, a team from the Chinese Academy of Sciences has been able to examine these complex high-order features in proteins that evolved separately but served a similar function.
“The findings emphasise an underrated sequence basis for functional trait convergence in evolution,” the team said in a paper published in the peer-reviewed journal Proceedings of the National Academy of Sciences on September 23.
Convergent evolution, also known as convergence, is the repeated, independent evolutionary emergence of the same trait in two or more species, thought to be driven by adaptation to similar environments or lifestyles.
