Defining the single base importance of human mRNAs and lncRNAs.
Rui FanXiangwen JiJianwei LiQinghua CuiChunmei CuiPublished in: Briefings in bioinformatics (2023)
As the fundamental unit of a gene and its transcripts, nucleotides have enormous impacts on the gene function and evolution, and thus on phenotypes and diseases. In order to identify the key nucleotides of one specific gene, it is quite crucial to quantitatively measure the importance of each base on the gene. However, there are still no sequence-based methods of doing that. Here, we proposed Base Importance Calculator (BIC), an algorithm to calculate the importance score of each single base 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 through single nucleotide variations. Moreover, the BIC score in The Cancer Genome Atlas 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 importance of human mRNAs and lncRNAs.
Keyphrases
- genome wide analysis
- genome wide identification
- genome wide
- endothelial cells
- copy number
- sars cov
- transcription factor
- pluripotent stem cells
- single cell
- deep learning
- healthcare
- escherichia coli
- papillary thyroid
- dna methylation
- cystic fibrosis
- staphylococcus aureus
- health information
- young adults
- social media
- biofilm formation
- bioinformatics analysis