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Contributions of genomics to life-history theory

Key Points

  • Life-history theory seeks to understand how evolutionary factors have shaped variation in life-history traits, both within and among organisms.

  • Life-history traits include such traits as age at first reproduction and reproductive effort, but, because they have direct impacts on these traits, life-history theory also deals with other traits such as body size.

  • A central assumption of life-history theory is that the most fit combination of trait values is determined by trade-offs among traits.

  • Much of the empirical research that stems from life-history theory is concerned with understanding how trade-offs arise.

  • Recent developments in genomics have enabled a dissection of the molecular underpinnings of trade-offs that are important to life-history evolution.

  • Genomic studies of trade-offs have shown that in many cases they arise because of the costs of up- or downregulation of gene expression.

  • Microarray analyses have indicated that changes in many genes could be involved in the expression of even dimorphic variation.

  • Life-history models typically predict single optima. Genomic analyses indicate that such optima might be attained by different suites of genes, and that different mechanisms can be involved in producing the same phenotypic end point.

Abstract

Life-history theory seeks to understand the factors that produce variation in life histories that are found both among and within species. At the organismal level there is a well developed mathematical framework, and an important focus of the current research is determining the biological underpinnings of this framework, with particular attention to the causal mechanisms that underlie trade-offs. Genomic approaches are proving useful in addressing this issue.

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Figure 1: Different molecular mechanisms can produce the same phenotype.

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Acknowledgements

This work was supported by the US National Science Foundation.

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Glossary

Pleiotropy

The influence of a locus on more than one trait.

Eigenvectors

The set of coefficients that define each principal component.

Eigenvalue

The variance of each principal component.

Linkage disequilibrium

The non-random association between two loci. This can be caused by physical linkage due to the two loci being on the same chromosome, or to disassortative mating.

Antagonistic pleiotropy

A negative genetic correlation between traits such that selection on one trait is opposed by the consequent selection on the second trait.

Dimorphic variation

Variation in which two distinct morphs can be identified (for example, wing dimorphism in insects).

Threshold model

The threshold model assumes that there is a normally distributed underlying trait, called the liability, plus a threshold: individuals above the threshold follow one developmental pathway, whereas individuals below the threshold follow the alternative pathway.

Holometabolous

A mode of development in insects in which there are discrete larval and pupal stages (as in Diptera and Lepidoptera).

Hemimetabolous

Insects in which development proceeds without a distinct pupal stage, with the nymphal stages moulting directly into the adult form (as in Hemiptera and Orthoptera).

Mutation accumulation

One hypothesis to account for senescence. Mutations accumulate during life as a result of errors that are incurred during sequential somatic cell divisions. Such mutations have deleterious effects on survival.

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Roff, D. Contributions of genomics to life-history theory. Nat Rev Genet 8, 116–125 (2007). https://doi.org/10.1038/nrg2040

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