Unprecedented advancements in next generation sequencing has allowed for careful cataloguing (e.g., databases such as ExAC, gnomAD, TopMed etc.) of genetic variants observed in large human populations. The availability of such catalogues of population-scale variants provides an important avenue for probing potential contributions of genetic variants towards genotype-to-phenotype variations in individuals. Despite CpG being an underrepresented (~ 3%) dinucleotide in the human genome, 18% of germline missense variants in human genome originate from CpG transitions alone. The hypermutable (6-fold higher-than-expected frequency) CpG transitions thus have a large contribution to the origin of variants in the human genome and proteome. As the proteome provides an important link between genotype and phenotype, there is a demanding need for systematic analyses of the impacts of CpG transitions on human proteome and protein function. Among all amino acids, the codons for arginine are altered more frequently by CpG transitions to result in a compositional bias, as 15% of human germline missense variants are arginine variants. The bias in germline variants thus perturbs arginine mediated interactions in proteins (e.g., DNA–protein interactions and transcriptional regulation) more than that of other amino acids. To better understand the molecular consequences of the bias, about 200 arginine missense variants observed in ExAC that can be mapped to known structures of human protein–DNA complexes of transcription factors were probed computationally using machine learning algorithms (mCSM and PremPDI). Our results suggest that germline arginine variants at both binding and non-binding sites of small DNA-binding-domains could potentially weaken (DDG &lt;&lt; 0) the protein–DNA interactions. CpG transitions thus have the potential to alter transcriptional network and provides a framework to probe the consequences of CpG transitions experimentally in future.

Predicting the impact of germ line mutations on protein DNA interactions

ACS Spring 2022

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