The theory of evolution by natural selection is sound and well-proven, but that doesn’t mean we won’t learn anything new about how life develops and changes over time. A new study suggests that evolution may not be as unpredictable as previously thought. The implications of this could open the way to new ways to tackle real-world problems including antibiotic resistance, disease and even climate change.
The study challenges the long-held belief that evolution is an unpredictable process. According to the study, the evolutionary trajectory of a genome may depend on its evolutionary past, rather than being determined by a variety of factors and historical accidents.
“The implications of this research are nothing short of revolutionary,” Professor James McInerney from the School of Life Sciences at the University of Nottingham explained in a statement. “By proving that evolution is not as random as we previously thought, we have opened the door to many possibilities in synthetic biology, medicine and ecology.”
McInerney and his colleagues analyzed the pangenome—a collection of all the DNA sequences of a given species, containing sequences common to all individuals—to answer a critical question: Can the evolutionary history of a genome determine its future trajectory?
The team used a machine learning method known as Random Forest with a data set of 2,500 complete genomes from a single bacterial species. To study this question, they spent several hundred thousand hours of computer processing.
By feeding the data into a computer, they were able to create “gene families” from every gene in every genome.
“In this way we were able to compare similar genomes,” added Maria Rosa Domingo-Sananes from Nottingham Trent University.
Once families were identified, it was possible to study how they were present in some genomes and absent in others.
“We found that some gene families never appeared in the genome if another gene family was already present there, and in other cases, some genes were very dependent on the presence of another gene family.”
Essentially, the study revealed an “invisible ecosystem” of genes that cooperate or compete with each other.
“These interactions between genes make some aspects of evolution somewhat predictable, and what’s more, we now have the tools to make these predictions,” Dr Domingo-Sananes added.
According to Dr Alan Bevan, also from the School of Life Sciences at the University of Nottingham, “Based on this work we can start to study which genes ‘maintain’, for example, the antibiotic resistance gene. So if we are trying to eliminate antibiotic resistance, we We can target not only the focal gene, but also the genes that support it.”
This approach can be used to synthesize new genetic constructs, “which could be used to develop new drugs or vaccines.” What we know now opens the door to many more discoveries,” Bevan added.
The implications are enormous and could lead to the creation of new genomes, with which scientists can design synthetic genomes and develop roadmaps for predictable manipulation of genetic material. They can also help scientists combat the rise of antibiotic resistance by helping us understand relationships between genes and create targeted treatments.
The findings could also influence the design of microorganisms designed to sequester carbon or decompose pollutants, which could help us combat climate change.
The study was published in the journal PNAS.