Extreme differences between human germline and tumor mutation densities are driven by ancestral human-specific...

Area of Science:

• Genomics
• Evolutionary Biology
• Cancer Research

Background:

• Mutation accumulation varies across the genome, with human germline and tumor mutation densities showing poor correlation.
• Genomic features are differentially associated with human germline and tumor mutation patterns.
• Understanding deviations from an ancestral mutational landscape is key to deciphering human-specific genomic processes.

Purpose of the Study:

• To identify human germline- and tumor-specific mutational landscape deviations using non-human great ape (NHGA) germlines as a reference.
• To investigate the correlation between tumor mutation density and NHGA germline mutation patterns.
• To elucidate the impact of human-specific evolutionary events on genome-wide mutation distribution.

Main Methods:

• Comparative genomics analysis of human and non-human great ape (NHGA) germline genomes.
• Assessment of mutation density correlations between human germlines, human tumors, and NHGA germlines.
• Analysis of mutation distribution at CpG and non-CpG sites to identify human-specific differences.

Main Results:

• Tumor mutation density distribution shows a stronger correlation with NHGA germlines than with human germlines.
• Human-specific differences in non-CpG site mutation distribution drive the observed divergence.
• Ancestral human demographic events and a human-specific mutation slowdown appear to have disrupted the ancestral genome-wide mutation density distribution.

Conclusions:

• Human tumors partially restore an ancestral-like mutation density distribution through somatic mutation accumulation.
• NHGA germline data offers a valuable alternative to human controls for establishing the expected mutational background of healthy somatic cells.
• This study provides novel insights into the evolutionary forces shaping human genome mutation patterns and their implications for cancer research.