Fig. 7: Models of gene interaction to explain phenotypic diversity in population. | Molecular Psychiatry

Fig. 7: Models of gene interaction to explain phenotypic diversity in population.

From: Phenotypic diversity is caused by non-linear genetic interactions between two SNAREopathy genes

Fig. 7: Models of gene interaction to explain phenotypic diversity in population.The alternative text for this image may have been generated using AI.

A Effects of pathogenic variation in two hypothetical genes (Α and Β) are represented as normally distributed severity of phenotypes that are shifted to the right relative to the normal (healthy) individuals, indicating pathogenicity. B Graphs from B.1 to B2.2. represent the predicted effects of the combination of variants in the two genes in one individual. B.1 Common pathway model: combinations of two variants in these genes are predicted to lead to phenotypes similar to the strongest single variant (αA or αB). The resulting distribution is similar, but not identical, to the distribution of the more severe of the two variants (αB); the distribution was identified by simulating pairs of normally distributed variables according to αA or αB, and selecting the maximal number. B.2.1 Additive interaction model: phenotypic severity in individuals with variants in two genes is represented as the summation of effects of single gene variants (αA + αB). If the effects of single gene variants follow a normal distribution (as represented in panel A), the effect of a combination of variants in two or more genes follows a normal distribution, according to an additive model of interaction. The vertical dashed line indicates 20% of most severe cases in an additive model with two hypothetical gene variants (αA and αB), called ‘moderate’ phenotype. The percentage of population with moderate phenotype according to each model is indicated. B.2.2 Multiplicative interaction model: phenotypic severity in individuals with variants in two genes is represented as the multiplication of the effects of single gene variants (αA * αB). If the effects of single gene variants follow the normal distribution, according to multiplicative model of interaction the effect of combination of the variants in more genes would be right-skewed, approaching lognormal distribution, with larger variance compared to additive model. The blank (non-filled) curves represent the effects of single gene variants, re-plotted from panel A. Vertical black dash-dash line is drawn to represent 20% of most severe cases of multiplicative model, called ‘severe’ phenotype. Vertical grey dash-dot-dash line is drawn to represent 10% of the least severe cases of multiplicative model, called ‘mild’ phenotype. The percentage of population with mild and severe phenotypes according to other models are represented within the respective graphs. Following parameters were used to generate a model: normal (mean = 0, s.d. = 0.1), variant in gene 1 (mean = 2, s.d. = 0.6), variant in gene 2 (mean = 4, s.d. = 1.4) on 1*106 random repetitions. Distribution fit was performed in MATLAB.

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