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Retrieving the deleterious mutations before extinction: genome-wide comparison of shared derived mutations in liver cancer and normal population


Study purpose Deleterious mutations would be rapidly purged from natural populations along with the extinction of their carriers. The currently observed mutations in existing species are mostly neutral. The inaccessibility of deleterious mutations impedes the functional studies on how these mutations affect the fitness at individual level.

Study design The connection between the deleterious genotype and the non-adaptive phenotype could be bridged by sequencing the genome before extinction. Although this approach is no longer feasible for evolutionary biologists, it is feasible for cancer biologists by profiling the mutations in tumour samples which are so deleterious that the carriers hardly live.

Results By comparing the derived mutation profile between normal populations and patients with liver cancer, we found that the shared mutations, which are highly deleterious, are suppressed to low allele frequencies in normal populations and tissues, but show remarkably high frequency in tumours. The density of shared mutations is negatively correlated with gene conservation and expression levels.

Conclusions Deleterious mutations are suppressed in functionally important genes as well as in normal populations. This work deepened our understanding on how natural selection act on deleterious mutations by analogising the cancer evolution to species evolution, which are essentially the same molecular process but at different time scales.

  • cancer genetics

Data availability statement

Data are available in a public, open access repository. The SNP data of the 1000 Genomes Project were downloaded from their official website ( The genome version is “phase2 reference assembly sequence hs37d5”. The genome of macaque (Macaca mulatta) is downloaded from the UCSC genome browser website ( The genome version is rheMac10. The liver cancer (hepatocellular carcinoma) transcriptome was downloaded from NCBI via accession number GSE112705. Patient ID LC502 was used.

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