Email updates

Keep up to date with the latest news and content from Genome Biology and BioMed Central.

Open Access Open Badges Research

Quantifying the major mechanisms of recent gene duplications in the human and mouse genomes: a novel strategy to estimate gene duplication rates

Deng Pan and Liqing Zhang*

Author Affiliations

Department of Computer Science, Virginia Tech, Torgerson Hall, Blacksburg, Virginia 24061-0106, USA

For all author emails, please log on.

Genome Biology 2007, 8:R158  doi:10.1186/gb-2007-8-8-r158

Published: 2 August 2007



The rate of gene duplication is an important parameter in the study of evolution, but the influence of gene conversion and technical problems have confounded previous attempts to provide a satisfying estimate. We propose a new strategy to estimate the rate that involves separate quantification of the rates of two different mechanisms of gene duplication and subsequent combination of the two rates, based on their respective contributions to the overall gene duplication rate.


Previous estimates of gene duplication rates are based on small gene families. Therefore, to assess the applicability of this to families of all sizes, we looked at both two-copy gene families and the entire genome. We studied unequal crossover and retrotransposition, and found that these mechanisms of gene duplication are largely independent and account for a substantial amount of duplicated genes. Unequal crossover contributed more to duplications in the entire genome than retrotransposition did, but this contribution was significantly less in two-copy gene families, and duplicated genes arising from this mechanism are more likely to be retained. Combining rates of duplication using the two mechanisms, we estimated the overall rates to be from approximately 0.515 to 1.49 × 10-3 per gene per million years in human, and from approximately 1.23 to 4.23 × 10-3 in mouse. The rates estimated from two-copy gene families are always lower than those from the entire genome, and so it is not appropriate to use small families to estimate the rate for the entire genome.


We present a novel strategy for estimating gene duplication rates. Our results show that different mechanisms contribute differently to the evolution of small and large gene families.