Artificial intelligence (AI) can detect and predict patterns that are hidden from the human eye and from conventional homology-detection tools. Enhancers are distal DNA cis-regulatory elements that regulate complex transcriptional repertoire. A natural language processing (NLP) model was trained using only six enhancer sequences from the Kaposi’s sarcoma-associated herpesvirus (KSHV) genome. This tool, termed ENHAvir, can identify known enhancers and predict novel enhancer elements in other herpesviruses, different viruses, and the human genome. The activity of the predicted enhancers in HSV-2, HCMV, HHV-6, HHV-7, and EBV was confirmed experimentally, enabling the creation of a comprehensive enhancer map of human herpesviruses. All human herpesviruses contain terminal repeats (TRs), which play important roles in cleaving the viral genome into genome-size units, genome encapsidation, and genome circularization following entry into the nucleus of a newly infected cell. This study adds another role for the TR of all human herpesviruses, a strong enhancer with the features of a “viral super enhancer”. Comparing herpesvirus enhancers with human enhancers revealed conserved enhancer signatures and the involvement of Alu elements. Here, an AI tool is presented that successfully predicts enhancers in both viral and human genomes.
- Nilabja Roy Chowdhury
- Deepanway Ghosal
- Meir Shamay
