Global Analysis of Human mRNA FOlding Disruptions in Synonymous Variants Demonstrates Significant Population Constraint

Background In most organisms the structure of an mRNA molecule is a crucial determinant of its speed of translation, half-life, splicing propensities and final configuration as a protein. Synonymous mutations which distort this wildtype mRNA structure may be pathogenic as a consequence. However, current clinical guidelines classify synonymous or “silent” single nucleotide variants (sSNVs) as largely benign unless a role in RNA splicing can be demonstrated. Results We developed novel software to conduct a global transcriptome study in which RNA folding statistics were computed for 469 million SNVs in 45,800 transcripts using an Apache Spark implementation of the ViennaRNA software package in the cloud. Focusing our analysis on the subset of 17.9 million sSNVs we discover that variants predicted to disrupt mRNA structure have lower rates of incidence in the human population. Given that the community lacks tools to evaluate the potential pathogenic impact of sSNVs, we introduce a “Structural Predictivity Index” (SPI) to quantify this constraint due to mRNA structure. Conclusion Our findings support the hypothesis that sSNVs may play a role in human genetic diseases due to their effects on mRNA structure. The SPI score and our computed Vienna metrics provide a means of gauging the structural constraint operating on any sSNV. Given that up to 75% of patients with a suspected rare genetic disease lack a molecular diagnosis, our score has the potential to enable discovery of novel etiologies in human genetic disease. Our RNA Stability Pipeline as well as Vienna structural metrics and SPI scores for all human synonymous SNPs can be downloaded from GitHub https://github.com/nch-igm/rna-stability.