Reduced Intrinsic DNA Curvature Leads to Increased Mutation Rate

Mutation is the ultimate source of genetic variation and plays an important role during evolution. The estimation of mutation rate and particularly, the identification of the trans factors and cis elements that regulate mutation rate have been the focus of evolutionary genetics for a long time. A large number of trans factors influencing mutation rate have been identified.

 

Cis elements likely play a more important role in determining the local mutation rate, yet remain poorly understood; cis elements identified so far have been limited to the scale of a few neighboring nucleotides around the mutation site.

 

Recently, researchers from QIAN Wenfeng’s Lab at the Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, those from HE Xionglei’s Lab at Sun Yat-sen University, and Prof. Lucas B. Carey at Universitat Pompeu Fabra collaborated to tackle this problem.

 

They characterized a high-density mutational landscape of yeast gene URA3 and calculated the correlation between each of the 17 DNA shape properties and the local mutation rate.

 

They identified a new cis element that determines the local mutation rate in both yeast and humans, intrinsic DNA curvature, which is defined as the deflection of DNA axis due to the interaction between neighboring base pairs. A 10% decrease in intrinsic DNA curvature results in a 70% increase in mutation rate. Consistently, both yeast and human tumors accumulate mutations in the regions with smaller curvature.

 

This effect is due to differences in the intrinsic mutation rate, likely due to differences in mutagen sensitivity, suggesting that DNA curvature reduces the mutation rate by promoting protein binding that makes DNA less accessible to mutagens.

 

This study establishes a framework for understanding the local mutation rate and offers new insights into genomic evolution and tumorigenesis.

 

This work entitled “Reduced intrinsic DNA curvature leads to increased mutation rate”, has been published in Genomics Biology (DOI: 10.1186/s13059-018-1525-y).

 

This work was supported by the National Natural Science Foundation of China.