For decades, the study of human evolution has primarily relied on the analysis of fossils, particularly bones, the only parts of the human body that are preserved over long periods of time. However, progress recent published in the journal Nature Ecology & Evolution opens a new door. It is indeed now possible to infer the genetic activity of non-skeletal tissues, such as the brain, from DNA methylation patterns in ancient specimens. This revolutionary method promises to transform our understanding of human evolution.
DNA methylation: a key indicator of genetic activity
The DNA methylation is an essential biological mechanism that regulates gene expression. This process adds small molecules (methyl groups) to parts of the DNA, acting like a switch that turns genes on or off. Unlike mutations which modify the genetic sequence itself, methylation does not alter the genetic code, but influences how it is read and used by cells.
This process plays a crucial role in the development of tissues and organs. For example, in the brain, it contributes to the differentiation of neurons and the formation of complex neuronal networks. However, tissues such as the brain are not preserved in the fossil record, making direct analysis of their genetic activity in ancient specimens previously impossible.
An innovative method for exploring the invisible
Faced with this limitation, a team of researchers led by Yoav Mathov and professors Liran Carmel and Eran Meshorer, from the Hebrew University of Jerusalem, developed a method to predict DNA methylation in unpreserved tissues. Their approach is based on a learning algorithm which is based on methylation data from living species. By analyzing DNA methylation patterns from skeletal tissues (like bones), this algorithm can infer how these patterns would manifest in other tissues, like the brain, with a remarkable accuracy reaching up to 92%.
This method was applied to ancient human specimens, allowing the recreation of methylation patterns in critical regions of the brain, such as the prefrontal cortex. The latter is an essential brain structure involved in complex functions such as planning, decision-making and self-awareness, typically human traits.
Discoveries about the evolution of the human brain
The application of this model made it possible to highlight more 1,850 differentiated methylation sites specifically in neurons of the prefrontal cortex. These sites are associated with genes essential for brain development, such as those of the NBPF family (neuroblastoma breakpoint family). These genes play a key role in regulating brain size, a characteristic that distinguishes modern humans from their ancestors and other primates.
The results of this work offer clues to the epigenetic mechanisms that contributed to the evolution of human cognitive abilities. They allow us to explore, for the first time, the biological adaptations that have shaped our brain by revealing how certain genes have seen their activity modified over time to support complex cognitive functions.
The implications of predicting DNA methylation beyond fossils
This method is not limited to the analysis of ancient human brains. It opens the way to the study of other non-preserved tissues such as the liver, muscles or even the heart in fossil specimens. It thus makes it possible to extend the field of evolutionary biology and to answer previously inaccessible questions.
The implications are vast. By studying how tissue-specific epigenetic modifications evolved, researchers can better understand the biological forces that have shaped not only our brains, but also other fundamental aspects of our anatomy and physiology. This approach could also offer insights into the origin of human diseases associated with the evolution of certain genetic traits.
Thus, this new revolutionary method does not just lift the veil on the evolution of our brain; it redefines the way we study the biological history of humanity. By making hidden mechanisms at the heart of our DNA visible, it opens up new horizons in the study of evolution and its impacts on complex human traits.
