Back

Genome-wide profiling of an enhancer-associated histone modification reveals the influence of asthma on the epigenome of the airway epithelium.

McErlean, P.; Kelly, A.; Dhariwal, J.; Kirtland, M.; Watson, J.; Ranz Jimenez, I.; Saxena, A.; Cousins, D.; Solari, R.; Edwards, M. R.; Johnston, S. l.; Lavender, P.

2019-06-27 genomics
10.1101/282889 bioRxiv
Show abstract

Asthma is a chronic airway disease driven by complex genetic-environmental interactions. The role of epigenetic modifications in bronchial epithelial cells (BECs) in asthma is poorly understood. We undertook genome-wide profiling of the enhancer-associated histone modification H3K27ac in BECs from people with asthma and healthy controls. We identified 49,903 regions exhibiting differential H3K27ac enrichment in asthma, clustered at genes associated with type-2-high asthma (CLCA1) and epithelial processes (EMT). Asthma dramatically influenced the BEC enhancer landscape and we identified asthma-associated Super-Enhancers encompassing genes encoding transcription factors (TP63) and enzymes regulating lipid metabolism (NOX4). We integrated published protein, epigenomic and transcriptomic datasets and identified epithelium-specific transcription factors associated with H3K27ac in asthma (TP73) and dynamic relationships between asthma-associated changes in H3K27ac, DNA methylation, genetic susceptibility and transcriptional profiles. Finally, we used a CRISPR-based approach to recapitulate the H3K27ac-asthma landscape in vitro and provide proof of principal that asthma-associated gene expression (SERPINB2) is driven in part by aberrant histone acetylation, validating the combination of genome-wide and epigenome-editing approaches in deciphering the molecular mechanisms underlying asthma pathogenesis.

Matching journals

The top 9 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.