Whole chromosome aneuploidy: big mutations drive adaptation by phenotypic leap

Abstract

Despite its widespread existence, the adaptive role of aneuploidy (the abnormal state of having an unequal number of different chromosomes) has been a subject of debate. Cellular aneuploidy has been associated with enhanced resistance to stress, whereas on the organismal level it is detrimental to multicellular species. Certain aneuploid karyotypes are deleterious for specific environments, but karyotype diversity in a population potentiates adaptive evolution. To reconcile these paradoxical observations, this review distinguishes the role of aneuploidy in cellular versus organismal evolution. Further, it proposes a population genetics perspective to examine the behavior of aneuploidy on a populational versus individual level. By altering the copy number of a significant portion of the genome, aneuploidy introduces large phenotypic leaps that enable small cell populations to explore a wide phenotypic landscape, from which adaptive traits can be selected. The production of chromosome number variation can be further increased by stress- or mutation-induced chromosomal instability, fueling rapid cellular adaptation.

Figure 1. Aneuploidy can exert opposing effect on overall body wellness and cellular fitness in disease

A: In tumorigenesis, the cellular fitness/proliferation of tumor tissue is enhanced at the expense of overall body wellness. B: Aneuploidy can have different roles on cellular versus organismal level. Organismal aneuploidy originates from karyotype alteration in parental germ line/gametes. Cellular aneuploidy results from errors in somatic cell mitosis.

Figure 2. Potent selection favors mutation with large phenotypic variation

A: The fitness distribution of two classes of mutations. Class A (red) and Class B (blue) generate different amounts of phenotypic variation (shown as the different characteristic widths a and b). For simplicity, we assume that both mutations have the same mode of skewed normal distribution of fitness (shown as varied resistance) and only one side of the distribution is shown. Under stress level x, only the mutants with a resistance level in the shaded area (survival probability α for Class A, β for Class B) can survive. B: Severe stress exaggerates the β/α ratio, and favors the survival of Class B mutants with large phenotypic variations. The 3-dimensional plot demonstrates that the survival probability of Class B mutants (β) relative to Class A mutants (α) increases with either enhancement of stress (x) or increase in phenotypic variation of Class B mutants relative to Class A mutants; the phenotypic variation is represented by characteristic width a and b, respectively. The stress level is normalized to the characteristic width a. For Class A mutation with a fitness distribution that has a characteristic width a, the survival probability α under stress level x is calculated as $$\alpha =\frac{1}{2}erfc\left(\frac{x}{\sqrt{2}a}\right)$$ where erfc denotes complementary error function. Class B mutation's probability of survival is calculated similarly.