CDsyn: A comprehensive database for deleterious human synonymous variation prediction

Synonymous variations, once considered irrelevant to gene regulation or disease progression, are now known to play a significant role in human diseases. We developed a one-stop resource, comprehensive database for deleterious synonymous variation prediction (CDsyn) to assess their significance and disease relevance. CDsyn encompasses six categories of information, including existing prediction scores, conservation scores, translation efficiency, sequence information, population frequency and other annotation information. With the assistance of CDsyn, we emphasize the significance of splicing mutation prediction score in identifying pathogenic synonymous mutations. Furthermore, we demonstrated the feasibility of developing a pathogenicity prediction algorithm for synonymous variations with CDsyn. In two practical tests, the CDsyn-comprehensive approach (along with its internal methods) outperformed both the SynMICdb and dbDSM databases, as well as the InterVar tool. CDsyn facilitates the prioritization of deleterious variants in clinical sequencing contexts and can enhance the understanding of synonymous variations in relation to human diseases.