For over a century, the reigning dogma in evolution has been that mutations — changes in the DNA — arise as blind accidents in the genome, leaving the survival of the fittest to separate the beneficial ones from the detrimental.
Now, groundbreaking research presents a fundamental challenge to that dogma, showing that nature’s most famous adaptive mutations do not arise randomly at all.
Despite the long-held belief that mutations are random, it has never been possible to observe individual mutations as they arise naturally. Prof. Adi Livnat of University of Haifa, director of the Sagol Lab for Evolution Research, lead author Dr. Daniel Melamed, and the team recently developed the most accurate mutation-detection method to date, crossing this barrier.
In a new study in the Proceedings of the National Academy of Sciences (PNAS), this team of scientists from Israel and Ghana showed that a mutation of major evolutionary importance, the APOL1 1024A>G mutation, which protects against the most common form of African sleeping sickness, while increasing the risk of kidney disease in people with two copies, originates de novo significantly more frequently exactly where it is needed: in sub-Saharan Africans compared to Europeans and in the precise location in the gene where it is protective.
“These results are completely unexpected from the random-mutation point of view. From that view, individual mutations are not supposed to arise more frequently where needed,” said Livnat.
These findings strikingly parallel the group’s earlier results showing that the HbS mutation, which protects against malaria while causing sickle cell anemia in homozygotes, originates de novo more frequently precisely in the gene and population where it is needed.
Two punches, one paradigm shift: with the HbS and APOL1 mutations — two of the most iconic examples of adaptive mutations in humans — the team has shown that these classic examples of “random mutation and natural selection” are, in fact, nonrandom.
Accident or directedness?
For a century, scientists assumed there were two basic ideas about how evolution occurs — (1) random mutations filtered by natural selection, and (2) Lamarckism — the idea that the organism directly senses its environment and somehow changes its genes to fit it.
Livnat’s theory moves away from both of these concepts, arguing instead that rather than random or Lamarckian, mutations are informed by the genome itself. A previously unrecognized internal force operates inside the organism, putting together genetic information that has accumulated internally in the genome over generations in useful ways.
To illustrate, take fusion mutations, where two genes fuse to form a new gene. As for all mutations, it has been thought that fusions arise by accident. But Livnat’s team recently showed that genes that have evolved to be used together repeatedly over generations are more likely to get fused. Because the genome folds in 3D space, bringing genes that work together to the same place and time in the nucleus, molecular mechanisms fuse these genes rather than others, “hardwiring” long-standing biological interactions into simplified genomic instructions.
Or take single-letter changes that are implemented by complex regulatory phenomena at each generation at the RNA level. The authors argue that these changes over the generations are more likely to be “hardwired” into the genome by mutation, simplifying regulation.
In the PNAS paper they argue that fusions and RNA editing are but two examples of a general principle that applies across mutation types. Rather than local accidents disconnected from other genetic information, mutations combine and integrate genetic information into streamlined instructions. Over the generations, and with feedback from natural selection, interconnected mutational activity enables long-term directed mutational responses to specific environmental pressures, as shown by the APOL1 and HbS mutations.
Simplifying information, along with gene duplication, creates modules that then themselves combine into higher-level interactions, driving evolutionary novelty.
Revisiting how evolution happens
The results suggest that mutations are not trivial outcomes of blind accidents as has been assumed for a century.
“Previous studies examined mutation rates as averages across genomic positions, masking the probabilities of individual mutations. But our studies suggest that, at the scale of individual mutations, each mutation has its own probability, and the causes and consequences of mutation are related,” says Livnat.
In the brain, pieces of information that are repeatedly used together in the course of learning become chunked together into a single piece that is thereafter activated as one. In evolution, genes that are used together over generations are more likely to be fused together by mutational mechanisms. “Not only are gene fusion mutations nonrandom, their mechanism of origination is actually analogous to one of the most basic principles of cognition and learning in the brain,” said Livnat.
That mechanisms like those in the brain govern the way life itself evolves shows that evolution is far more sophisticated than previously imagined. Together with the new, high-resolution view of the origination of individual mutations, this opens up a vast new world to be explored at the core of how evolution happens, allowing scientists to investigate how mutations arise across the genome and to delve deeper into their mechanisms of origination.
The study was funded by the John Templeton Foundation, the Israel Science Foundation, and the Sagol Network through the Sagol Lab for Evolution Research.
The study appeared in the September 2 issue of PNAS.
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