UC San Diego AI Model Identifies Initiator Sequence in 60% of Human Genes from 500,000 Variants Tested
UC San Diego researchers used AI trained on 500,000 synthetic initiators to decode the DNA motif that initiates transcription in 60% of human genes. The model enables mutation-effect prediction and synthetic promoter engineering relevant to cancer and gene therapy. Evidence strength rests on in vitro sequencing data; cellular and in vivo validation remain pending.
Next steps include integrating the initiator model with chromatin and transcription-factor binding maps to test whether predicted initiator strength correlates with measured RNA output in primary human cells. If validated, the framework could prioritize which promoter mutations warrant functional follow-up in patient-derived organoids within the next 18 months.
Kadonaga lab: Within 24 months, the initiator model will correctly rank mutation effects on promoter activity for at least 10 cancer driver genes in patient-derived cell lines with >75% concordance to experimental measurements.
Sources (2)
- [1]Primary Source(https://www.science.org/doi/10.1126/science.adp1234)
- [2]Supporting Source(https://www.nature.com/articles/s41588-024-01789-3)