The Complexity of Genetic Redundancy


Genetic redundancy is often associated with the duplication of an open reading frame within a genome or a multiplicity of regulatory elements sharing a target. Genetic redundancy is inferred when the modification or deletion of a portion of functional genetic material results in minimal changes to a trait or organismal phenotype – robustness – and when this genetic information is surplus to a reference, non‐robust, genome. Robustness has been attributed to buffering mechanisms promoted by duplicates and to compensatory pathways that can be independent of duplication. Most redundant duplicates are rapidly lost from genomes by mutation and drift. The preservation of redundancy requires some form of epistasis or pleiotropy, typically evolving through subfunctionalization of gene products. The term redundancy is too coarse to capture the full range of phenomena that it is used to describe and new concepts are required for dealing with multi‐locus and context‐dependent robustness.

Key Concepts:

  • Redundancy arises through mechanisms that compensate for the loss of functional genetic information.

  • Redundancy can be achieved through a duplication of a structural or regulatory gene.

  • Redundancy arises neutrally through partial or whole‐genome duplication and can persist without selection for short periods of time.

  • The long‐term preservation of redundancy requires specific genetic mechanisms, epistastis or pleiotropy, and on‐going selection pressures.

  • Redundancy is most common in species found in small populations with large genomes for whom neutral processes, dominated by drift, play a significant role.

  • Genetic or structural similarity among perturbed (knockout or knockdown) duplicates, to imply functional interchangeability, is empirically the strongest predictor of genetic redundancy.

  • Alternative, functionally equivalent pathways, that do not share genetic duplicates, can provide mechanisms of redundancy.

  • Redundancy is context‐dependent and often involves numerous factors to include epigenetic modification, environmental compensation, not just genetic loci.

  • Recent studies showing a very high incidence of loss‐function variants in human genomes provide strong support for the prevalence of mechanisms of redundancy.

  • New concepts are required to capture the robustness of genomes that go beyond mechanisms of redundancy. These new concepts will need to deal effectively with the contribution of numerous loci and factors – collective robustness.

Keywords: robustness; canalisation; genome architecture; evodevo; regulatory network; evolution; subfunctionalization

Figure 1.

Convergent activation and nonspecific negative feedback can lead to functional redundancy in a gene regulatory network. Proteins A and B are transcription factors produced at an equal rate and capable of activating the expression of gene C. Gene A activates C at a rate ka and gene B activates C at a rate kb. Gene C can be thought to work according to three different negative feedback mechanisms: (1) encode a protein capable of inhibiting the production of A and B, (2) encode a protein inhibiting the activation of C by A and B or (3) increase the decay of A and B mRNA. In all three cases the inhibitory influence of C is given by the rate constant kc. All three proteins are degraded at an equal rate d. We are interested in the steady state concentration of C following the knockout of A in comparison with the steady state concentration of C in the wildtype (in which A and B are both present). The ratio of mutant to wild‐type concentration of C assuming feedback mechanisms (1) and (2) is given by kb/ka+kb. If we assume that ka=kb, then the reduction in steady state concentration of C is about 30%. The steady state ratio assuming feedback mechanism (3) depends on the rate of protein decay d. When the decay rate is very small (d→0), then the ratio is equal to 1. In other words, the circuit is completely redundant with respect to the loss of A. When the decay rate is very fast (d→∝) then for ka=kb, the ratio of mutant to wildtype is 0.5. For realistic rates of decay, the ratio remains approximately equal to 1. This toy model shows that for a range of negative feedback mechanisms, this network structure produces a degree of functional redundancy greater than the additive contribution of individual genes.



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Further Reading

Ihmels J, Collins SR, Schuldiner M, Krogan NJ and Weissman JS (2007) Backup without redundancy: genetic interactions reveal the cost of duplicated genes. Molecular System Biology 3: 1–11.

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Krakauer, David C(Dec 2014) The Complexity of Genetic Redundancy. In: eLS. John Wiley & Sons Ltd, Chichester. [doi: 10.1002/9780470015902.a0006116.pub3]