Trade-offs and Pleiotropy

In genetics, pleiotropy can be defined as one gene affecting multiple traits, or more specifically a single mutation having a consequence on multiple aspects of the organism’s phenotype. Developmental body plans are largely pleiotropic, such that they are controlled by the same genetic architecture. An allele that increases height in males will most likely increase height in females, or a mutation that increases left arm length will also increase right arm length due to the intrinsic overlap in these developmental processes. Or negatively, sprinters with genes that promote the growth of fast-twitch muscle fibres will inhibit the development of slow-twitch fibres, and vise versa for naturally born long-distance runners.

The extent of the interaction within the genome is slowly coming into realization, in the form of the human interactome. This describes the physical and indirect network of protein, nucleic acids, lipids and carbohydrate interactions that culminate in the overall functioning and regulation of each cell. Pleiotropy becomes extremely relevant in the context of complex disease, where the interaction between the combination of many small effect polymorphisms (genes with small difference between individuals) accumulate into a spectrum of disease severity. This is shown in the following graphical representation of the proteins that interact to comprise the pathophysiology of autism.

“Isoform interactions: Proteins encoded by autism candidate genes (red nodes) interact with many more proteins (blue and yellow lines) than previously thought (gray lines)”

However, to gain more of an understanding of pleiotropy outside of molecular biology, we need to frame it in the context of environmental pressures. Firstly, species are likely to inhabit different environments within their life and among multiple generations, which change what it means to be ‘fit’ over time and space. Subsequently, not all genotypes are created equal; or rephrased, not all mutational difference in the genome provide equal performance under different environments. This is the concept of Genotype-by-Environment interaction (GxE), where different environments dictate the generation of different phenotypes for the same underlying genotype (ie. plants increasing the number of leaves they produce in response to increasing sunlight intensities in different environments).

If you’re struggling to understand this concept (which is apparently quite difficult to explain in words), you’re not the only one, as this interaction is the result of an extremely complex system of which we still know little about. An example of a way in which the genome and environment can interact is presented in this Khan Academy video, or in this diagram below:

Genotype-by-Environment interaction in its simplest form. Source: Khan Academy


In this sense, generalist species exhibit minimal GxE interaction, conserving their phenotype across different conditions and making them suitable to varying environments. However, specialists have a definitive peak in fitness under a specific environment, making them more adept to specific, stable environmental conditions. Specialist therefore show higher levels of GxE interaction, which can mean that genes that allow high fitness in one environment can dramatically decrease fitness in another environment. This is called antagonistic pleiotropy, a genetic trade-off for organisms.

The Lenski Experiment:

This was a long-term experimental evolution study, consisting of 12 replicate lines of E. coli (figuratively understood as parallel universes for evolution). The results showed that the strains that had replicated for ~66,000 generations at 37°C (specialists) had evolved an increased division rate (proxy for fitness) at this temperature compared to the ancestral strain. However, their division rate was comparatively inferior to the ancestral strain (generalists) at temperatures greater than 39°C, highlighting that antagonistic pleiotropy of the growth rate adaptations had diminished their ability to perform basic cellular activities at non-optimal temperatures (environments).

Antagonistic pleiotropy is especially prevalent in life history traits, which involve lifetime events such as birth, age of reproductive maturity and number of offspring produced. This is determined by the organism’s relative investment of resources into survival and growth, or reproduction. In a natural setting, this trade-off can be seen for Trinidad and Tobago guppies living in different springs.

Trinidad & Tobago Guppy Manipulation Experiment:

Females living in low predation environments were found to use their finite available resources to produce few but larger (more viable) offspring, due to their higher probability of survival. However, females in springs with a high number of predators hedged their bets and produced a large number of smaller offspring, utilitarianistically increasing their chances of reaching sexual maturity and bearing offspring themselves. Transplanting guppies from high to low predation sites resulted in a decrease in the number, and an increase in size off the offspring. This highlighted the concept of phenotypic plasticity, that the same genome can generate alternative traits under different environments, as well as identifying that genome is pleiotropically constrained (through its finite resources) against producing many large offspring.

Similarly for males, there is an inherent trade-off between survival and mate seeking, as is exemplified with male cricket behavior.

The ‘live fast, die young’ Experiment:

To attract potential partners, males run their hind legs against their abdomen to produce the call that we have become so accustomed to each evening. This is not only metabolically costly, but alerts their presence to predators. A study in Nature found that male crickets ‘live fast and die young’, as the energy-intensive night calling efforts resulting in lower longevity, even in the absence of predation. However, if this allocation of resources towards calling effort was capable of finding a mate to reproduce with within their shorter lifespan, then it is still a viable life history strategy.

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