A new study led by Professor James McInerney and Dr. Alan Beavan from the University of Nottingham suggests that evolution may not be as random as previously thought. The researchers analyzed the pangenome, the complete set of genes within a species, to identify patterns influenced by a genome’s history.
The team used machine learning algorithms to sift through a massive dataset of 2,500 complete genomes from a single bacterial species. They created “gene families” and focused on the interactions between genes and gene families. The results showed that some genes never turned up in a genome when another specific gene family was already present, while others were highly dependent on the presence of different gene families.
This discovery reveals an invisible ecosystem where genes interact with each other, making evolution somewhat predictable. According to Dr. Maria Rosa Domingo-Sananes, “These interactions between genes make aspects of evolution somewhat predictable and furthermore, we now have a tool that allows us to make those predictions.”
The implications of this research are significant, with potential applications in tackling issues like antibiotic resistance, diseases, and climate change. By understanding the network of genes that work together, scientists can develop more effective treatments and potentially create new drugs or vaccines.
The study’s insights might also help in the fight against climate change by engineering microorganisms that can capture carbon or break down pollutants. Additionally, personalized medicine could become more precise with this knowledge, allowing doctors to predict how a disease might progress in a patient’s body based on their genetic makeup.
This research opens up new avenues in medicine and environmental science, challenging our fundamental assumptions about life and evolution. With the potential for predicting and guiding evolutionary changes, the possibilities are vast and exciting.
Source: https://www.earth.com/news/discovery-evolution-not-random-gene-families-pangenome-influence-called-revolutionary