An integrated genomics approach towards deciphering human genome codes shaping HIV proviral transcription and fate

HIV integrates semi-randomly into the genome of immune cells and thus proviruses that persist in patients under long-term, highly active suppressive therapy can be detected in various positions (inside and outside) and orientations (same, convergent and divergent) respective to genes, promoters, and enhancers. Thus, this integration landscape heterogeneity can influence HIV transcription activity thereby dictating proviral fate (active vs latent). However, the effect of the integration site to proviral transcription activity has so far remained elusive. Here we integrate open-source, large-scale datasets including epigenetics, transcriptome, and 3D genome architecture to interrogate the chromatin states, transcription activity landscape, nuclear sub-compartments, and topological associated domains around HIV integration sites in CD4+ T cell-based models to decipher ‘codes’ in the human genome shaping proviral transcription. As part of this integrated approach, here we collect nucleosome occupancy profiles in Jurkat CD4+ T cells. Nucleosome occupancy profiles in the Jurkat derivative J-Lat 10.6 T cell line.