Multivariate analysis of genomic variables, effective population size, and mutation rate

BMC Res Notes. 2019 Jan 25;12(1):60. doi: 10.1186/s13104-019-4097-3.

Abstract

Objective: The relationship between genomic variables (genome size, gene number, intron size, and intron number) and evolutionary forces has two implications. First, they help to unravel the mechanism underlying genome evolution. Second, they provide a solution to the debate over discrepancy between genome size variation and organismal complexity. Previously, a clear correlation between genomic variables and effective population size and mutation rate (Neu) led to an important hypothesis to consider random genetic drift as a major evolutionary force during evolution of genome size and complexity. But recent reports also support natural selection as the leading evolutionary force. As such, the debate remains unresolved.

Results: Here, we used a multivariate method to explore the relationship between genomic variables and Neu in order to understand the evolution of genome. Previously reported patterns between genomic variables and Neu were not observed in our multivariate study. We found only one association between intron number and Neu, but no relationships were observed between genome size, intron size, gene number, and Neu, suggesting that Neu of the organisms solely does not influence genome evolution. We, therefore, concluded that Neu influences intron evolution, while it may not be the only force that provides mechanistic insights into genome evolution and complexity.

Keywords: Genetic drift; Genome evolution; Genomic variables; Multivariate analysis.

MeSH terms

  • Animals
  • Datasets as Topic
  • Genetic Drift
  • Genetics, Population*
  • Genome / genetics*
  • Genome Size / genetics
  • Genomics / methods*
  • Humans
  • Introns / genetics
  • Multivariate Analysis
  • Mutation Rate*
  • Population Density*