Scientists from the Centre for Genomic Regulation in Barcelona have found that the initial regions of genes—so-called transcription start sites—are the most prone to mutations. The findings were published in Nature Communications (NatCom).

The researchers analyzed more than 225,000 genomes from participants in the UK Biobank and the gnomAD database, as well as data from family-based studies. The highest number of mutations was detected in the “starting” regions of genes associated with cancer, brain function, and developmental disorders.

The analysis showed that the first 100 base pairs immediately after the start of a gene mutate about 35% more often than expected. Gene bases (nitrogenous bases) are molecules that make up nucleotides—the repeating building blocks of DNA.

It is from these regions that the cell begins reading DNA to synthesize RNA, so any changes here can have a substantial impact on gene function. According to the authors, these zones are among the most functionally important regions of the entire genome, on par with protein-coding sequences.

The researchers also found that a significant proportion of mutations arise at the very earliest stages of embryonic development—during the first cycles of cell division after conception. Such changes are known as mosaic mutations: they are present only in a subset of the body’s cells. As a result, these mutation “hotspots” long remained undetected by standard genetic analyses.

Mosaic mutations are particularly important from a clinical perspective. In a parent, they may cause no symptoms, but when transmitted through germ cells, the child receives the mutation in all cells of the body, increasing the risk of disease.

The authors further showed that most of these mutations are eventually eliminated by natural selection and therefore rarely persist in the population. This discovery is important for medical genetics: existing models of mutation assessment underestimate the “background” level of changes in these regions. Incorporating the new data will allow for more accurate interpretation of genetic tests and help avoid false conclusions when searching for the causes of inherited diseases.