Defining the single base importance of human mRNAs and lncRNAs

Abstract

As the fundamental unit of a gene and its transcripts, nucleotides have enormous impacts on molecular function and evolution, and thus on phenotypes and diseases. Given that different nucleotides on one gene often exhibit diverse levels of effects, it is quite crucial to comprehensively and quantitatively measure the importance of each base on a gene transcript, however, tools are still not available. Here we proposed Base Importance Calculator (BIC), an algorithm to calculate the importance score of single bases based on sequence information of human mRNAs and long noncoding RNAs (lncRNAs). We then confirmed its power by applying BIC to three different tasks. Firstly, we revealed that BIC can effectively evaluate the pathogenicity of both genes and single bases by analyzing the BIC scores and the pathogenicity of single nucleotide variations (SNVs). Moreover, the BIC score in the Cancer Genome Atlas (TCGA) somatic mutations is able to predict the prognosis of some cancers. Finally, we show that BIC can also precisely predict the transmissibility of SARS-CoV-2. The above results indicate that BIC is a useful tool for evaluating the single base important of human mRNAs and lncRNAs. Key PointsO_LIBIC could measure the single base importance of human mRNAs and lncRNAs. C_LIO_LIBIC could be applied to many aspects including measuring the pathogenicity of SNVs and enhancing the ability of predicting cancer survival. C_LIO_LIBIC could predict the transmissibility of SARS-CoV-2 C_LI