In this project, we aim to investigate the molecular basis of HIV-1 antisense transcripts associated with its latency. We will manipulate barcoded wildtype HIV-1 and conduct experiments using several “omics” technologies, including B-HIVE, RNA-seq, ChIP-seq, ATAC-seq, MNase-seq, HIV-1-capture HiC followed by high-throughput sequencing to characterize the molecular microenvironments of the latent HIV reservoir, especially those harboring proviruses at a deeper level of latency. Lastly, we will integrate these multidimensional datasets generated in this project to establish a deep learning-based quantitative model, enabling the prediction of the likelihood of the molecular microenvironments of the latent HIV reservoir. The candidate will be involved in above in daily task.