New Insight: Forces Driving Evolution Less Accidental Than Believed

Genetic mutations occur randomly, which makes evolution in many ways unpredictable. However, recent studies show that this is not entirely true, and interactions between genes play a bigger role than expected in determining how the genome changes.

It is known that some sections of the genome are more prone to mutations than others, but a new study also suggests that the evolutionary history of the species can affect the predictability of mutations.

“This study has revolutionary consequences,” emphasizes James Macinnerny, an evolutionary biologist from the University of Nottingham.

“Having shown that evolution is not as accidental as we thought before, we opened the door to many opportunities in synthetic biology, medicine, and ecology.”

Biologist Alan Beavan and his colleagues from the University of Nottingham used the computational power of artificial intelligence to explore more than 2000 complete bacteria genomes E. coli.

Bacteria are especially cunning when it comes to changing their DNA, as they know how to steal genes from the environment and include them in their genome. This process is called horizontal transfer of genes and gives bacteria the ability to quickly obtain new properties, such as resistance to antibiotics, without the need to wait until natural selection works for several generations.

It is interesting that horizontally transferred genes belonging to the same main group may be in different positions of the bacteria genome. By exploring horizontal genes in different places, scientists were able to observe how the environment affects them.

They were able to test the thought experiment of the famous evolutionary biologist Steven J. Gulda: if you repeat the tape of evolutionary history, each time it will result in a different, unpredictable outcome, as evolutionary paths depend on unpredictable events.

If this is true, then the bacterium’s genome will continue to evolve randomly after acquiring a new horizontal gene. However, artificial intelligence discovered patterns of predictability among thousands of these “repetitions

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