Effect of mutation mechanisms on variant composition and distribution in Caenorhabditis elegans

Ho Yon Hwang, Jiou Wang

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


Genetic diversity is maintained by continuing generation and removal of variants. While examining over 800,000 DNA variants in wild isolates of Caenorhabditis elegans, we made a discovery that the proportions of variant types are not constant across the C. elegans genome. The variant proportion is defined as the fraction of a specific variant type (e.g. single nucleotide polymorphism (SNP) or indel) within a broader set of variants (e.g. all variants or all non-SNPs). The proportions of most variant types show a correlation with the recombination rate. These correlations can be explained as a result of a concerted action of two mutation mechanisms, which we named Morgan and Sanger mechanisms. The two proposed mechanisms act according to the distinct components of recombination rate, specifically the genetic and physical distance. Regression analysis was used to explore the characteristics and contributions of the two mutation mechanisms. According to our model, ~20–40% of all mutations in C. elegans wild populations are derived from programmed meiotic double strand breaks, which precede chromosomal crossovers and thus may be the point of origin for the Morgan mechanism. A substantial part of the known correlation between the recombination rate and variant distribution appears to be caused by the mutations generated by the Morgan mechanism. Mathematically integrating the mutation model with background selection model gives a more complete depiction of how the variant landscape is shaped in C. elegans. Similar analysis should be possible in other species by examining the correlation between the recombination rate and variant landscape within the context of our mutation model.

Original languageEnglish (US)
Article numbere1005369
JournalPLoS computational biology
Issue number1
StatePublished - Jan 2017

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Modeling and Simulation
  • Ecology
  • Molecular Biology
  • Genetics
  • Cellular and Molecular Neuroscience
  • Computational Theory and Mathematics


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