Intragenic compensation through the lens of deep mutational scanning

Abstract

A significant fraction of mutations in proteins are deleterious and result in adverse consequences for protein function, stability, or interaction with other molecules. Intragenic compensation is a specific case of positive epistasis when a neutral missense mutation cancels effect of a deleterious mutation in the same protein. Permissive compensatory mutations facilitate protein evolution, since without them all sequences would be extremely conserved. Understanding compensatory mechanisms is an important scientific challenge at the intersection of protein biophysics and evolution. In human genetics, intragenic compensatory interactions are important since they may result in variable penetrance of pathogenic mutations or fixation of pathogenic human alleles in orthologous proteins from related species. The latter phenomenon complicates computational and clinical inference of an allele's pathogenicity. Deep mutational scanning is a relatively new technique that enables experimental studies of functional effects of thousands of mutations in proteins. We review the important aspects of the field and discuss existing limitations of current datasets. We reviewed ten published DMS datasets with quantified functional effects of single and double mutations and described rates and patterns of intragenic compensation in eight of them.

Supplementary information: The online version contains supplementary material available at 10.1007/s12551-022-01005-w.

Keywords: Deep mutational scanning; Epistasis; Intragenic compensation.

Fig. 1

Output of a DMS study of the Yap1 protein (Araya et al. 2012). Heatmap presents fitness scores of single substitutions. X axis: sequence positions, Y axis: amino acid residues. Grey cells denote missing values, the wild-type amino acid is denoted with black circle. Red and blue cells correspond to reduced and elevated fitness scores, respectively, measured as the binary logarithm of functional activity divided by the activity of the wild-type protein

Fig. 2

Density plots of fitness scores of single substitutions in the ten DMS datasets. Blue: deleterious ($S<-1$), grey: mild deleterious ($-1\le S<0$), red: neutral ($S\ge 0$)

Fig. 3

Output of a DMS study of the Yap1 protein (Araya et al. 2012). Heatmap of number of double substitutions. X and Y axes represent sequence positions, cells are colored according to the total number of pairs formed by AAS at these positions

Fig. 4

Compensated deleterious and other single AAS in ten DMS datasets. Datasets are sorted by decreasing overall size. DLG4_HUMAN and FOS_HUMAN were excluded from the analysis