A new study, published in Science, has used computational analysis to reveal the mechanisms behind germline mutations. Their findings have uncovered a set of responsible biological processes that will greatly develop our understanding of heritable mutations.
Human germline mutations
The biological mechanisms that underlie human germline mutations are largely unknown. Despite extensive research into mutagenesis, where and how these mutations occur has remained a mystery. As these mutations can cause severe heritable diseases, such as cystic fibrosis and Huntington’s disease, it is critical that they are better understood.
In this study, researchers explored the variation of mutation rate along the genome to model germline mutagenesis. In total, 292 million very rare single nucleotide variants (SNVs) were analysed using this model. From the analysis, the team discovered mutational processes that were associated with distinct genomic features.
“Genetic mutations are a rare yet inevitable and, indeed essential, part of the development and propagation of the human species – they create genetic diversity, fuel evolution, and occasionally cause genetic diseases,” lead investigator Shamil Sunyaev said.
“Harnessing the power of computation and big data, we analysed genomic variations and identified a set of biologic processes responsible for the vast majority of heritable human mutations.”
Processes that drive germline mutations
The analysis of the dataset revealed nine processes from which the majority of germline genetic mutations tended to arise. Eight processes correlated exclusively with one or two genomic features, including gene bodies, replication timing, direction of replication and chromatin accessibility. It was also found that, on average, processes had a 40% higher correlation with genomic features than any individual trinucleotide mutation type did.
DNA demethylation
One process identified by the dataset analysis, represented by C to G transversions, was found to be related to DNA demethylation. DNA demethylation is a common occurrence in early embryogenesis as part of epigenetic reprogramming. However, when it goes wrong, problems can arise. An intermediate product of demethylation is hydroxymethylated cytosines. In this study, when hydroxymethylated cytosines were not repaired, C to G point mutations increased in frequency. This mutation mechanism was predominantly seen in early mosaic mutations, likely driven by the high levels of demethylation in early development.
Furthermore, the researchers discovered that DNA methylation was also related to observed C-G to T-G mutations. When cytosine is methylated, it results in 5-methylcytosine. In this study, the team found that erroneous replication over 5-methylcytosine bases mediated the C-G to T-G mutations. In addition, deamination of 5-methylcytosine resulted in the conversion of cytosine to thymine. These results show that methylation plays a substantial role in mediating mutations.
Mutations in oocytes
Surprisingly, one identified mechanism was not related to DNA copying or cellular division – two processes usually prone to mutations. Instead, the discovered mutagenic process was dominated by C to G point mutations on the non-transcribed DNA strand in oocytes. The team interpreted this as transcription-associated mutagenesis that is possibly induced by localised susceptibility to DNA damage.
In addition, the oocyte mutations had a strong correlation with maternal age. Accumulation of maternal mutations with age in non-dividing oocytes cannot typically be mediated by replication. Therefore, previous studies have suggested that double strand breaks (DSBs) are a likely mechanism for such mutations. However, this study found that DSBs only contributed to a minority of the C to G point mutations, suggesting that DSBs are not a major mechanism.
Next steps
The work carried out in this study represents one of the most comprehensive computational efforts to explore germline mutations. Their findings have revealed previously unknown mechanisms behind heritable genomic variations.
The research team behind this study are now working to incorporate their results into a model of human-mutation rate along the genome. Their goal is to predict the chance that a specific mutation will occur at a specific genomic location. Hopefully, this work will develop our understanding of rare heritable diseases and how to treat them.
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