A new study challenges the long-standing idea that evolution is always random, and that this could have huge implications for solving life-changing problems.
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 studythe 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 University of Nottingham’s School of Life Sciences 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 DNA sequences from a given species, containing sequences common to all individuals – to answer a critical question: Can a genome’s evolutionary history determine its future trajectory?
The team used a machine learning method known as Random Forest with a dataset of 2,500 complete genomes from a single bacterial species. To study this question, they spent hundreds of thousands of hours on computer processing.
By entering the data into a computer, they were able to create “gene families” of each gene in each genome.
“In this way we could 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 work together 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 University of Nottingham’s School of Life Sciences: “Based on this work, we can start to study which genes, for example, ‘maintain’ the antibiotic resistance gene. So if we’re trying to eliminate antibiotic resistance, we can target not just the focal gene, but also the genes that support it.”
This approach could 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, allowing scientists to 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 the relationships between genes and develop targeted treatments.
The findings could also influence the design of microorganisms designed to capture carbon or break down pollutants, which could help us fight climate change.
The research was published in the journal PNAS.
